Database Training Courses

Database Training

Database Courses

Testi...Client Testimonials

SQL in SQL Server

Lukasz (the trainer) was very knowlegable and importantly adaptable to the different levels of knoweldge in the room, tailoring help and teaching on an individual level which was great. Very open and apporachable, being informativite, clear and providing good mechanisms for genuine understanding of the material provided.

Thomas Houiellebecq- Ernst & Young AG

Oracle Application Express Introduction

The format was really good, the exercises were not too difficult and helped us to fully understand the tool.

Juan Salvador Rios Hoyos- Oracle

MongoDB for Administrators

monitoring

Ling Xiao - The Globe and Mail

Oracle 11g - Programming with PL / SQL I - Workshops

very high competence of the trainer!!

Heino Eilers - Nokia Solutions And Networks

MongoDB for Administrators

Good content and exercises

Richard Smallwood - PayPoint Network Limited

MongoDB for Developers

open mind and communication

Oleksiy Deliyev - Insight Enterprises

PostgreSQL for Administrators

Trainer Subject Knowledge

Julian Pirau - BMO Financials

Oracle SQL Intermediate

Trainer provided some topic and support it with plenty of exercises. We had a chance to apply knowledge by doing them on our own.

- UBS Business Solutions Poland Sp. z o.o.

Oracle SQL Intermediate

Access to trainers individual support in resolving exercises.

Tomasz Czornak - UBS Business Solutions Poland Sp. z o.o.

PostgreSQL for Administrators

How to maintain the database, and how is the orgenazition of the data.

Jiang Chang - NAV CANADA

Fundamentals of Cassandra DB

- Trainer had good practical knowledge about using cassandra day-to-day at least for development purposes
- Catering (snacks, coffee hour) were great
- 3 days length was good

Mika Linnanoja - Rovio

Oracle 11g - SQL language for developers - Workshop

good atmosphere during the training

clovis Nebouet - HSBC Service Delivery; ITEKNA POLSKA Sp. z o.o.

MongoDB for Developers

super athmosphere, working with mongo shell

Jan Sturm - AVL List GmbH

MariaDB Database Administration

Training material was very informative. Learned a lot

Yaw Asamoah - FEDERAL AVIATION ADMINISTRATION

MariaDB Database Administration

lessons and examples

Kelly Taylor - FEDERAL AVIATION ADMINISTRATION

MariaDB Database Administration

he adapted to the experience of the group - gave us great value for a beginners course.

Rich Mickey - FEDERAL AVIATION ADMINISTRATION

MongoDB for Administrators

The structure and pace of the class was great.

David Lacy - Availity

MongoDB for Administrators

The depth of the Mongo db training was explored from basic to advanced, I felt it was a little too much to squeeze into 2 days but I did get exposure to all aspects of Mongo db.

Bay Sayarath - Availity

MongoDB for Administrators

Relevant to need.

Damon Grube - Availity

MongoDB for Administrators

Most of the hands on stuff was good.

Andrew Bauer - Availity

MongoDB for Administrators

I had attended a different training given by the mongo team. I like this one a lot better in terms of simplicity and course material. Thanks for helping us out.

Patience, clear and to the point.

V. Rai - New Jersey

MongoDB for Developers

He (the trainer) used good real world examples and pitched the exercises at the right level

Martin Davies- Capgemini UK Plc

PostgreSQL for Administrators

I liked everything he taught.

Emily Zhou - Ryerson University

PostgreSQL for Administrators

I wish we could had a lab time, maybe the amount of time of training is tighten, we did not have lab time in class.

Gary Pan - Ryerson University

Introduction to SQL Server 2012 Integration Services (SSIS)

The thorough / hands-on knowledge the trainer has

Pieter Peirs - ING BE

Developing Desktop Applications with Visual Studio 2012, VB.NET and SQL Server 2012

I appreciated Fulvio's wide breadth of knowledge. Not only was he familiar with the course content, but he also knew of constructs in languages we were familiar with to make examples more meaningful to us. During intervals he shared his knowledge of technologies and solutions outside the training scope to provide insights into other solutions we could use in future (and future training).

Raphael Keymer - Markit Valuations Limited

MariaDB Database Administration

Enjoyed the pace, delivery and technical knowhow of the trainer

Junaid Kalang - Capita CSL

PostgreSQL Administration and Development

Very in depth knowledge on the subject matter. No "I'll have to look into that and get back to you, just knew it all"

David Marshall - TIO Networks CORP

SQL Fundamentals

The trainer, he was knowledgeable, engaging, and easy to learn from. he encouraged a lot of hands on learning

Shawn McAndrew - Halifax Regional Municipality

Oracle 11g - SQL language for developers - Workshop

I like fact, that after each section we had exercises. It helps to remember discused topic.

Adam Bińczycki - HSBC Delivery; ALTEN Polska Sp. z o.o.; Mindbox S.A.; HSBC Delivery

SQL Fundamentals

I learned a LOOOOOT

Kamil Szmid - UBS Business Solutions Poland Sp. z o. o.

Cassandra for Developers

Topics approached. Very complete.

Carlos Eloi Barros - Farfetch Portugal - Unipessoal, Lda

Cassandra for Developers

The last exercise was very good.

José Monteiro - Farfetch Portugal - Unipessoal, Lda

Cassandra for Developers

I already using and have a application in production with cassandra so mostly of the topics i already know but the data modeling and advanced topics are a lot interesting.

Tiago Costa - Farfetch Portugal - Unipessoal, Lda

Cassandra for Developers

There was a lot of knowledge and material shared that will help me to do my current tasks.

Miguel Fernandes - Farfetch Portugal - Unipessoal, Lda

Cassandra for Developers

The amount of exercises. We could immediately apply the knowledge shared and ensure the information was on point.

Joana Pereira - Farfetch Portugal - Unipessoal, Lda

Cassandra for Developers

All technical explanation and theoretical introduction

André Santos - Farfetch Portugal - Unipessoal, Lda

Cassandra for Developers

Very good explanations with in depth examples

Rui Magalhaes - Farfetch Portugal - Unipessoal, Lda

Cassandra for Developers

The practical exercises and examples of implementing examples of real models and contexts

Leandro Gomes - Farfetch Portugal - Unipessoal, Lda

Building Web Apps using the MEAN stack

The labs were interesting and probably the most useful learning tool to me. Anything I missed or forgot about was relearned or reinforced in the labs.

Joseph Fuerst - The Aerospace Corporation

MongoDB for Administrators

tailored to cover our organisations questions.

Robin Bell - Egress Software Technologies

MongoDB for Administrators

The clear depth of knowledge the trainer had, which really shone when combined with his evident enthusiasm for the subject.

Joseph Brailsford - Egress Software Technologies

MongoDB for Administrators

Even though I have been using MongoDB for a while, there were still some new "basic" things that Kamil taught us - as well as teaching us the advanced topics we need to move our projects forwards.

Adam McKay - Egress Software Technologies

A practical introduction to Data Analysis and Big Data

Willingness to share more

Balaram Chandra Paul - MOL Information Technology Asia Limited

Data Analysis with Hive/HiveQL

Liked very much the interactive way of learning.

Luigi Loiacono - Proximus

Data Analysis with Hive/HiveQL

It was a very practical training, I liked the hands-on exercises.

Proximus

Data Analysis with Hive/HiveQL

good overview, good balance between theory and exercises

Proximus

Data Analysis with Hive/HiveQL

Dynamic interaction and "hands on" the subject, thanks to the Virtual Machine, very stimulating!

Philippe Job - Proximus

Data Analysis with Hive/HiveQL

The competence and knowledge of the trainer

Jonathan Puvilland - Proximus

Advanced SQL, Stored Procedures and Triggers for Microsoft SQL Server

Attention to detail, knowledge and enthusiasm for the subject

Bristol City Council

Advanced SQL, Stored Procedures and Triggers for Microsoft SQL Server

Attention to detail, knowledge and enthusiasm for the subject

Bristol City Council

Advanced SQL, Stored Procedures and Triggers for Microsoft SQL Server

Attention to detail, knowledge and enthusiasm for the subject

Bristol City Council

Advanced SQL, Stored Procedures and Triggers for Microsoft SQL Server

Attention to detail, knowledge and enthusiasm for the subject

Bristol City Council

Advanced SQL, Stored Procedures and Triggers for Microsoft SQL Server

Attention to detail, knowledge and enthusiasm for the subject

Bristol City Council

Cassandra Administration

The 1:1 style meant the training was tailored to my individual needs.

Andy McGuigan - Axon Public Safety UK Limited

Transact SQL Advanced

The ability to ask questions at any time and the more informal / less structured style. This allowed us to pursue the areas of knowledge we were most interested in.

Jim Lane - Bristol City Council

A practical introduction to Data Analysis and Big Data

It covered a broad range of information.

Continental AG / Abteilung: CF IT Finance

MongoDB for Administrators

The explanations

Lowe's

A practical introduction to Data Analysis and Big Data

presentation of technologies

Continental AG / Abteilung: CF IT Finance

Redis for Developers and System Administrators

training knowledge and techinic

Sutiipong Bumlungvech - The Enterprise Resources Training Co., Ltd.

A practical introduction to Data Analysis and Big Data

Overall the Content was good.

Sameer Rohadia - Continental AG / Abteilung: CF IT Finance

Beyond the relational database: neo4j

Flexibility to blend in with Autodata related details to get more of a real world scenario as we went on.

Autodata Ltd

Beyond the relational database: neo4j

Flexibility to blend in with Autodata related details to get more of a real world scenario as we went on.

Autodata Ltd

Beyond the relational database: neo4j

The trainer did bring some good insight and ways to approach developing a graph database. He used examples from the slides presented but also drew on his own experience which was good.

Autodata Ltd

Beyond the relational database: neo4j

The trainer did bring some good insight and ways to approach developing a graph database. He used examples from the slides presented but also drew on his own experience which was good.

Autodata Ltd

Subcategories

Database Course Outlines

Code Name Duration Overview
transsqlbas Transact SQL Basic 14 hours Delegates will gain an understanding of the basic principles of Structured Query Language as well as being able to do each of the following: Construct queries to extract and filter data from a SQL Server database Create summarised results Change, derive and format data to suit the required output Change data and maintain database components and definitions This course is for anybody who needs information from a Microsoft SQL Server database. It is suitable for either system developers or people from other areas who need to use SQL to extract and analyse data. Basics Selection of all columns/fields Selection of certain columns/fields Use of distinct/unique Selection of certain rows/records Selection of values in a range Selection of values matching a pattern mask Selection of values within a list Treatment of null values How to sort and order data Selection of calculated and derived values How to control column headings in query results How to send query results to external files Joining Tables Principles of joining tables: Use of cartesian join Use of inner join Use of non-equi join Use of outer join Joining Queries Union operator Intersect operator Except operator Simple Functions Conversion functions Date functions Number functions Text functions Group/summary/aggregate functions Sub-Queries Principles of sub-queries How to filter rows from main query Use of nested sub-query Use of multi-column sub-query Use of correlated sub-query Use of sub-query as an inline view and common table expression Use of sub-query as a column in main query Case Statements Principles of case statements Use of case statement to derive column values Use of nested case statements Use of case statements to produce pivot tables Use of case statement with sub-queries Data Manipulation How to insert values into a table How to copy values between tables How to update values How to delete records How to change data via views Use of transactions How to lock rows and tables Data Definition Principles of a relational database and data normalisation Use of primary key and foreign key relationships and constraints How to create tables How to alter tables How to create views Use of synonyms How to remove tables and views
67592 SQL Server 2008 Administration 28 hours This SQL Server Administration training course teaches students how to administer a SQL Server 2008. Objectives Install and configure Microsoft SQL Server Create databases and tables Implement indexes and partitions Take database snapshots Implement service broker for asynchronous processing of database requests Create and use full-text indexes Secure SQL Server and implement policy-based management Recover data Automate administrative tasks with the SQL Server Agent Use Dynamic Management Views to monitor the database and troubleshoot problems Configure a SQL Server for high availability using failover clustering, database mirroring, log shipping, and replication Overview of Microsoft SQL Server 2008 Database Engine Business Intelligence Installing and Configuring SQL Server 2008 Editions of SQL Server Infrastructure Requirements Service Accounts Collation Sequences Authentication Modes SQL Server Instances Upgrading to SQL Server Installing SQL Server Using the Tools in SQL Server 2008 SQL Server Documentation Management Tools in SQL Server Performance Management Tools Business Intelligence Tools Creating Databases SQL Server System Databases SQL Server Database Structure Creating a Database Moving Databases Designing Tables Naming Objects Schemas Data Types Column Properties Creating Tables Computed Columns Sparse Columns Constraints Database Diagrams Indexes Index Structure Clustered Indexes Nonclustered Indexes Included Columns Filtered Indexes Online Index Creation Index Management and Maintenance XML Indexes Spatial Indexes Partitioning Partition Functions Partition Schemes Partitioning Tables and Indexes Managing Partitions Database Snapshots Creating a Database Snapshot Reverting Data Using a Database Snapshot Service Broker Service Broker Architecture Message Types and Contracts Queues and Services Conversations Sending and Receiving Messages Queue Activation Prioritization Full-Text Indexing Full-Text Catalogs Full-Text Indexes Querying Full-Text Data Security Configuring the Attack Surface Endpoints Principals, Securables, and Permissions CLR Security Data Encryption Policy-Based Management Overview of Policy-Based Management Facets Conditions Policy Targets Policies Policy Categories Policy Compliance Data Recovery Database Backups Recovery Models Database Restores SQL Server Agent Creating Jobs Creating Maintenance Plans Creating Alerts Dynamic Management Views Overview of DMVs Retrieving Object Metadata Database Diagnostics High Availability Failover Clustering Database Mirroring Log Shipping Replication
373 Oracle Database 11g: New Features for Administrators DBA Release 2 28 hours Oracle Restart Controlling Oracle Restart Using the srvctl Utility Manually Adding Components to the Oracle Restart Configuration ASM Enhancements Setting up ASM fast mirror resync Using ASM Scalability and Performance Enhancements ASM Disk Group Compatibility Using ASMCMD Extensions ASM File Access Control ASM Optimal Disk Placement Storage Enhancements Using 4 KB-Sector Disks Using Table Compression Hybrid Columnar Compression SQL Access Advisor Segment Creation on Demand Data Warehouse and Partitioning Enhancements Preprocessing Data for ORACLE_LOADER Access Driver in External Tables Degree of Parallelism Enhancements In-Memory Parallel Query Partitioning Enhancements System-Managed Indexes for List Partitioning SQL Performance Analyzer SQL Performance Analyzer: Overview Using SQL Performance Analyzer Using Enterprise Manager to Access SQL Performance Analyzer SQL Performance Analyzer: Data Dictionary Views Database Replay Using Database Replay Database Replay System Architecture Supported Workloads Database Replay Workflow in Enterprise Manager Database Replay PL/SQL Procedures Database Replay Data Dictionary Views Automatic SQL Tuning Automatic SQL Tuning in Oracle Database 11g Selecting Potential SQL Statements for Tuning Controlling the Automatic SQL Tuning Task Configuring Automatic SQL Tuning Using the PL/SQL Interface to Generate Reports Intelligent Infrastructure Enhancements Using New Automatic Workload Repository Views Creating AWR Baselines Defining Alert Thresholds Using Static Baseline Controlling Automatic Maintenance Tasks Fixed Policy CPU Resource Management Scheduler Enhancements Diagnosability Enhancements Setting Up Automatic Diagnostic Repository ADRCI: The ADR Command-Line Tool Using the Enterprise Manager Support Workbench Running Health Checks Manually Using the SQL Repair Advisor SQL Monitoring SQL Monitoring in Oracle Database 11g Release 2 Viewing Session Details Viewing the SQL Monitoring Report Performance Enhancements Using the DBMS_ADDM Package New and Modified Views Enabling Automatic Memory Management Using New Statistic Preferences Features Locking Enhancements Adaptive Cursor Sharing Using Table Annotation to Control Result Caching Application Maintenance and Upgrade Enhancements Online Redefinition Enhancements Creating and Using Invisible Indexes Backup and Recovery Enhancements Using New SET NEWNAME Clauses Optimized Backups Using New Settings for Binary Compression Enhancements to Database Duplication Creating Archival Backups TSPITR Enhancements and Modifications Creating and Using Virtual Private Catalogs Flashback Technology, LogMiner, and Data Pump Oracle Total Recall Flashback Transaction Backout Enterprise Manager LogMiner Interface Data Pump Legacy Mode Data Recovery Advisor Assessing Data Failures Data Recovery Advisor RMAN Command-Line Interface Data Recovery Advisor Views
bigdatastore Big Data Storage Solution - NoSQL 14 hours When traditional storage technologies don't handle the amount of data you need to store there are hundereds of alternatives. This course try to guide the participants what are alternatives for storing and analyzing Big Data and what are theirs pros and cons. This course is mostly focused on discussion and presentation of solutions, though hands-on exercises are available on demand. Limits of Traditional Technologies SQL databases Redundancy: replicas and clusters Constraints Speed Overview of database types Object Databases Document Store Cloud Databases Wide Column Store Multidimensional Databases Multivalue Databases Streaming and Time Series Databases Multimodel Databases Graph Databases Key Value XML Databases Distribute file systems Popular NoSQL Databases MongoDB Cassandra Apache Hadoop Apache Spark other solutions NewSQL Overview of available solutions Performance Inconsitencies Document Storage/Search Optimized Solr/Lucene/Elasticsearch other solutions
PentahoDI Pentaho Data Integration Fundamentals 21 hours Pentaho Data Integration is an open-source data integration tool for defining jobs and data transformations. In this instructor-led, live training, participants will learn how to use Pentaho Data Integration's powerful ETL capabilities and rich GUI to manage an entire big data lifecycle, maximizing the value of data to the organization. By the end of this training, participants will be able to: Create, preview, and run basic data transformations containing steps and hops Configure and secure the Pentaho Enterprise Repository Harness disparate sources of data and generate a single, unified version of the truth in an analytics-ready format. Provide results to third-part applications for further processing Audience Data Analyst ETL developers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us.
dbalogicmigration Database Logic Migration 7 hours When migrating databases there are common ways of dealing with logic put either in SQL queries specific to the database or database procedural language (e.g. PL/SQL). This course covers techniques and strategies of making migration smooth. Also it deals with possible performance and scalability problems. This course is usually deliver with following databases: DB2, Oracle, MySQL, MariaDB, SQL Server, etc... but can be tailored to a specific migration project. Database Logic analysis and problems Where to find logic How to distinguish logic which should be migrated out of database and the logic which can stay Scalability issues Creating unit tests Migration strategies analysis - pros and cons Flexibility vs speed Speed vs scalability Procedural Language to Service PL to PL Removing intermediate derived data (cash) and replacing with life logic OLTP vs Warehouse Design of new logic adapter service Using traditional programming Using Rule Engines or other Logic Engines Unit Testing Performance and scalability issues Changing Client Site ORM (Object-relations mapping) frameworks Using web-service output instead of a query or stored procedure Performance testing Profiling (finding bottlenecks and performing optimisation)
mlbankingr Machine Learning for Banking (with R) 28 hours In this instructor-led, live training, participants will learn how to apply machine learning techniques and tools for solving real-world problems in the banking industry. R will be used as the programming language. Participants first learn the key principles, then put their knowledge into practice by building their own machine learning models and using them to complete live team projects. Introduction Difference between statistical learning (statistical analysis) and machine learning Adoption of machine learning technology by finance and banking companies Different Types of Machine Learning Supervised learning vs unsupervised learning Iteration and evaluation Bias-variance trade-off Combining supervised and unsupervised learning (semi-supervised learning) Machine Learning Languages and Toolsets Open source vs proprietary systems and software R vs Python vs Matlab Libraries and frameworks Machine Learning Case Studies Consumer data and big data Assessing risk in consumer and business lending Improving customer service through sentiment analysis Detecting identity fraud, billing fraud and money laundering Introduction to R Installing the RStudio IDE Loading R packages Data structures Vectors Factors Lists Data Frames Matrixes and Arrays How to Load Machine Learning Data Databases, data warehouses and streaming data Distributed storage and processing with Hadoop and Spark Importing data from a database Importing data from Excel and CSV Modeling Business Decisions with Supervised Learning Classifying your data (classification) Using regression analysis to predict outcome Choosing from available machine learning algorithms Understanding decision tree algorithms Understanding random forest algorithms Model evaluation Exercise Regression Analysis Linear regression Generalizations and Nonlinearity Exercise Classification Bayesian refresher Naive Bayes Logistic regression K-Nearest neighbors Exercise Hands-on: Building an Estimation Model Assessing lending risk based on customer type and history Evaluating the performance of Machine Learning Algorithms Cross-validation and resampling Bootstrap aggregation (bagging) Exercise Modeling Business Decisions with Unsupervised Learning K-means clustering Challenges of unsupervised learning Beyond K-means Exercise Hands-on: Building a Recommendation System Analyzing past customer behavior to improve new service offerings Extending your company's capabilities Developing models in the cloud Accelerating machine learning with additional GPUs Beyond machine learning: Artificial Intelligence (AI) Applying Deep Learning neural networks for computer vision, voice recognition and text analysis Closing Remarks
3134 Oracle Application Express Introduction 21 hours Audience Course aimed at developers Format of the course 35% lectures, 65% labs Introducing  Application Express What is Application Express(APEX)? Benefits of APEX History of APEX Architecture Overview – logical and physical APEX Repository Overview Out of the box development features SQL Developer and APEX Building integrated applications Integrating APEX & BI Publisher Getting Started with Application Express What is a Workspace? Different types of APEX users Application Express Components What is a packaged application? Creating a workspace and a developer Working with the SQL Workshop What is SQL Workshop? Browsing, creating and modifying Objects Processing ad hoc SQL and PL/SQL statements Managing scripts Using Query Builder to build queries graphically Creating an Application Components of an application Page Definition Application Builder Home Page An Application’s Home Page Creating an application from scratch Creating an application from a spreadsheet Understanding Application Builder Application Builder Defaults Developer's Preferences User Interface Defaults Application Groups Workspace Themes Managing export repository Understanding Pages and Regions What is a Page in APEX? Controls on a Page Different Sections of a Page Page Rendering Page Processing Shared Components Attributes of a Page What is a Region? Different Attributes of a Region Creating Reports (Part 1) Creating SQL Reports SQL Report Attributes SQL Report Column Attributes Creating Reports (Part 2) Creating Interactive Reports Interactive Report Attributes Interactive Report Column Attributes Creating Forms Creating Forms with Report Creating Simple Forms Creating Tabular Forms Creating Master-Detail Forms Creating Forms Using Wizards and Manually Understanding Page Rendering & Page Processing Components Required for a Form Working with Items & Buttons Creating Different Types of Items (Text, Text Area, Checkbox, Select List, Radio Group etc.) Creating Buttons Understanding Different Attributes of an Item and Button to Control its Look & Feel, Positioning and Functionality Working with Shared Components Creating Tabs, Lists, Breadcrumbs, Navigation Bar, List of Values Understanding Different Attributes of Shared Components Using Shared Components in Pages Page Rendering & Processing Computations Validations Processes Branches Creating Calendars Easy Calendar SQL Calendar Understanding Different Attributes of a Calendar Creating Charts Understanding Different Types of Charts Creating Charts Understanding Different Attributes of a Chart Page Zero, Themes & Templates What is Page Zero Creating Page Zero Understanding Themes Switching Themes Changing Theme Defaults Understanding Templates and viewing template definitions Developer's Toolbar, Session State, Debugging & Troubleshooting Understanding Different Options on Developer's Toolbar Understanding Session State Management Understanding Sessions & Session IDs Referencing Session States in the Application Security Understanding Different Authentication Options in APEX Creating a Custom Authentication Switching from One Authentication Method to Another Understanding Authorization in APEX Creating Authorization Schemes Attaching Authorization Schemes to Pages, Regions, Tabs etc. Packaging & Deploying Application Understanding Different Deployment Options Understanding the Packaging & Deployment Process Packaging Application with Supporting Objects Deploying Application from One Environment to Another
66437 Microsoft SQL Server 2008/2012 (MSSQL) 14 hours This course has been created for delegates already acquainted with SQL in Microsoft SQL Server Environment 2008/2012. The course focuses on set-based querying and query tuning, working with indexes and analyzing execution plans. The training also covers table expressions, ranking functions and how to deal with partitioned tables. Module 1. Query Tuning Tools for Query Tuning Cached Query Execution Plans Clearing the Cache Analyzing Execution Plans Hints Using the Database Engine Tuning Advisor Index Tuning Table and Index Structures Index Access Methods Indexing Strategies Module 2. Subqueries, Table Expression, and Ranking Functions Writing Subqueries Using Table Expressions Using Ranking Functions Module 3. Optimizing Joins and Set Operations Fundamental Join Types Join Algorithm Set Operations Using INTO with Set Operation Module 4. Aggregating and Pivoting Data Using the OVER Clause Different types of aggregations (Cumulative, Sliding and Year-To-Date) Pivoting and Unpivoting Setup Custom Aggregations Using GROUPING SETS Subclause CUBE and RULLUP Subclauses How to materialize Grouping Sets Module 5. Using TOP and APPLY SELECT TOP Using the APPLY table operator TOP n at the Group Level Implementing Paging Module 6. Optimizing Data Transformation Inserting data with Enhanced VALUES Clause Using the BULK Rowset Provider Using INSERT EXEC The Sequence Mechanisms DELETE with joins UPDATE with joins MERGE statement The OUTPUT Clause with INSERT The OUTPUT Clause with DELETE The OUTPUT Clause with UPDATE The OUTPUT Clause with MERGE Module 7. Querying Partitioned Tables Partitioning in SQL Server How to write queries on partitioned tables How to write queries on partitioned views
aerosdev Aerospike for Developers 14 hours This course covers everything a database developer needs to know to successfully develop applications using Aerospike.Data Management Data Model Primary Index Secondary Index Hybrid Storage Distribution Data Distribution Consistency Guarantees Clustering Cross Data-Center Replication Rack Awareness Client Architecture ACID Key-Value Store Single Record Batch Scans Policies Data Types Lists Maps Geospatial Large Data Types Query User-Defined Functions Record UDF Stream UDF Aggregation Security (Enterprise Edition only) Known Limitations
hbasedev HBase for Developers 21 hours This course introduces HBase – a NoSQL store on top of Hadoop.  The course is intended for developers who will be using HBase to develop applications,  and administrators who will manage HBase clusters. We will walk a developer through HBase architecture and data modelling and application development on HBase. It will also discuss using MapReduce with HBase, and some administration topics, related to performance optimization. The course  is very  hands-on with lots of lab exercises. Duration : 3 days Audience : Developers  & Administrators Section 1: Introduction to Big Data & NoSQL Big Data ecosystem NoSQL overview CAP theorem When is NoSQL appropriate Columnar storage HBase and NoSQL Section 2 : HBase Intro Concepts and Design Architecture (HMaster and Region Server) Data integrity HBase ecosystem Lab : Exploring HBase Section 3 : HBase Data model Namespaces, Tables and Regions Rows, columns, column families, versions HBase Shell and Admin commands Lab : HBase Shell Section 3 : Accessing HBase using Java API Introduction to Java API Read / Write path Time Series data Scans Map Reduce Filters Counters Co-processors Labs (multiple) : Using HBase Java API to implement  time series , Map Reduce, Filters and counters. Section 4 : HBase schema Design : Group session students are presented with real world use cases students work in groups to come up with design solutions discuss / critique and learn from multiple designs Labs : implement a scenario in HBase Section 5 : HBase Internals Understanding HBase under the hood Memfile / HFile / WAL HDFS storage Compactions Splits Bloom Filters Caches Diagnostics Section 6 : HBase installation and configuration hardware selection install methods common configurations Lab : installing HBase Section 7 : HBase eco-system developing applications using HBase interacting with other Hadoop stack (MapReduce, Pig, Hive) frameworks around HBase advanced concepts (co-processors) Labs : writing HBase applications Section 8 : Monitoring And Best Practices monitoring tools and practices optimizing HBase HBase in the cloud real world use cases of HBase Labs : checking HBase vitals
hdp Hortonworks Data Platform (HDP) for administrators 21 hours Hortonworks Data Platform is an open-source Apache Hadoop support platform that provides a stable foundation for developing big data solutions on the Apache Hadoop ecosystem. This instructor-led live training introduces Hortonworks and walks participants through the deployment of Spark + Hadoop solution. By the end of this training, participants will be able to: Use Hortonworks to reliably run Hadoop at a large scale Unify Hadoop's security, governance, and operations capabilities with Spark's agile analytic workflows. Use Hortonworks to investigate, validate, certify and support each of the components in a Spark project Process different types of data, including structured, unstructured, in-motion, and at-rest. Audience Hadoop administrators Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us.  
datapyth Data Analysis in Python using Pandas and Numpy 14 hours Day 1 Data Analysis with pandas Using vectorized data in pandas Data wrangling Sorting and filtering data Aggregate operations Analyzing time series Data visualisation Plotting diagrams with matplotlib Using matplotlib from within pandas Creating quality diagrams Visualizing data in Jupyter notebooks Other visualization libraries in Python   Day 2 Vectorizing Data in Numpy Creating Numpy arrays Common operations on matrices Using ufuncs Views and broadcasting on Numpy arrays Optimizing performance by avoiding loops Optimizing performance with cProfile Other Python libraries for data analysis scikit-learn Scipy statsmodel RPy2
mlbankingpython_ Machine Learning for Banking (with Python) 21 hours In this instructor-led, live training, participants will learn how to apply machine learning techniques and tools for solving real-world problems in the banking industry. Python will be used as the programming language. Participants first learn the key principles, then put their knowledge into practice by building their own machine learning models and using them to complete live team projects. Introduction Difference between statistical learning (statistical analysis) and machine learning Adoption of machine learning technology and talent by finance and banking companies Different Types of Machine Learning Supervised learning vs unsupervised learning Iteration and evaluation Bias-variance trade-off Combining supervised and unsupervised learning (semi-supervised learning) Machine Learning Languages and Toolsets Open source vs proprietary systems and software Python vs R vs Matlab Libraries and frameworks Machine Learning Case Studies Consumer data and big data Assessing risk in consumer and business lending Improving customer service through sentiment analysis Detecting identity fraud, billing fraud and money laundering Hands-on: Python for Machine Learning Preparing the Development Environment Obtaining Python machine learning libraries and packages Working with scikit-learn and PyBrain How to Load Machine Learning Data Databases, data warehouses and streaming data Distributed storage and processing with Hadoop and Spark Exported data and Excel Modeling Business Decisions with Supervised Learning Classifying your data (classification) Using regression analysis to predict outcome Choosing from available machine learning algorithms Understandind decision tree algorithms Understanding random forest algorithms Model evaluation Exercise Regression Analysis Linear regression Generalizations and Nonlinearity Exercise Classification Bayesian refresher Naive Bayes Logistic regression K-Nearest neighbors Exercise Hands-on: Building an Estimation Model Assessing lending risk based on customer type and history Evaluating the performance of Machine Learning Algorithms Cross-validation and resampling Bootstrap aggregation (bagging) Exercise Modeling Business Decisions with Unsupervised Learning K-means clustering Challenges of unsupervised learning Beyond K-means Exercise Hands-on: Building a Recommendation System Analyzing past customer behavior to improve new service offerings Extending your company's capabilities Developing models in the cloud Accelerating machine learning with GPU Beyond machine learning: Artificial Intelligence (AI) Applying Deep Learning neural networks for computer vision, voice recognition and text analysis Closing Remarks
3119 Business Intelligence in MS SQL Server 2008 14 hours Training is dedicated to the basics of create a data warehouse environment based on MS SQL Server 2008. Course participant gain the basis for the design and construction of a data warehouse that runs on MS SQL Server 2008. Gain knowledge of how to build a simple ETL process based on the SSIS and then design and implement a data cube using SSAS. The participant will be able to manage OLAP database: create and delete database OLAP Processing a partition changes on-line. The participant will acquire knowledge of scripting XML / A and MDX. basis, objectives and application of data warehouse, data warehouse server types base building ETL processes in SSIS basic design data cubes in an Analysis Services: measure group measure dimensions, hierarchies, attributes, development of the project data cubes: measures calculated, partitions, perspectives, translations, actions, KPIs, Build and deploy, processing a partition the base XML / A: Partitioning, processes and overall Incremental, delete partitions, processes of aggregation, base MDX language
3457 Oracle 11g - Application Tuning - Workshop 28 hours For who The workshop is intended for advanced programmers and Oracle users who seek knowledge and information on the efficient development of information systems in an Oracle database, and the tuning and testing of performance issues in existing applications. This course builds on knowledge often unavailable or incorrectly presented in the technical documentation, and collected during many years of practice leading them instructors. These workshops may be the end of the training path for developers, or a single step for people with extensive experience designing and programming in Oracle Purpose of training The workshop aims to provide mechanisms that occur in an Oracle database when performing SQL statements. Allows participants to avoid errors during software development, and explore, diagnose, and resolve performance problems in existing applications. Particular emphasis is placed on the workshops, where we show the methodology and the practical aspects of the application and tuning SQL statements. The content of the training Mechanics perform SQL commands Managing the process cost optimization Methods of data storage and indexing Monitoring database performance and processes based on dictionaries and track system applications Analysis of cases of the most common problems that cause performance Notes The workshops are based on the software version 11g XE Application Tuning Methodology Architecture database and instance Server processes Memory structure (SGA, PGA) Parsing and share cursors The data files, log files, parameter files Analysis of the command execution plan Hypothetical plan (EXPLAIN PLAN, SQLPlus AutoTrac XPlane) The actual execution plan (V $ SQL_PLAN, XPlane, AWR) Monitoring the performance and find bottlenecks in the process Monitoring the current status of the instance by system dictionary views The monitoring of historical dictionaries Tracking application (SQLTrace, TkProf, TreSess The optimization process Properties cost optimization and regulated Determination to optimize Control work cost-based optimizer by: Session parameters and instance Tips (hints) Patterns of query plans Statistics and Histograms Impact statistics and histograms for performance The methods of collecting statistics and histograms Strategy of counting and estimating statistics Management statistics: blocking, copying, editing, automation of collection, monitoring changes Dynamic data sampling (temporary plates, complex predicates) Multi-column statistics, based on expressions Statistics System The logical and physical structure of the database Spaces tables. segments Extensions (EXTENTS) Blocks Data storage methods The physical aspects of the table temporary Tables Tables index external Tables Partition Table (span, letter, hash, mixed) Physical reorganization of tables Materialized views and mechanism QUERY REWRITE Methods of data indexing Building B-TREE indexes Properties index Indexes: a unique, multi-column, function, inverse Compression indices Reconstruction and merging indexes Virtual indexes Indexes private and public Bitmap Indexes and junction Case study - full-scan data The impact of a place at the table level and block performance readings Loading Data conventional and direct path The order of predicates Case Study - access to data via the index Methods of reading index (UNIQUE SCAN RANGE SCAN FULL SCAN FAST FULL SCAN MIN / MAX SCAN) Using functional indices The selectivity index (Clustering Factor) Multi-column indexes and SKIP SCAN NULL and indexes Index tables (IOT) Impact indices DML operations Case Study - sorting Sorting memory Sort index Sort linguistic The effect of entropy to sort (Clustering Factor) Case Study - joins and subqueries The merger: MERGE, HASH, NESTED LOOP Joins in OLTP and OLAP systems The order of switching Outer Joins AntI-join Joins incomplete (SEMI) Subqueries simple Correlated subqueries The views, the WITH clause Other operations cost-based optimizer Buffer Sort INLIST VIEW FILTER Count Stop Key Result Cache Inquiries dispersed Read query plans for use dblinks Choosing the leading mark Parallel processing
berkeleydb Berkeley DB for developers 21 hours Berkeley DB (BDB) is a software library intended to provide a high-performance embedded database for key/value data. Berkeley DB is written in C with API bindings for C++, C#, Java, Perl, PHP, Python, Ruby, Smalltalk, Tcl, and many other programming languages. Berkeley DB is not a relational database.[1] This course will introduce the architecture and capabilities of Berkeley DB and walk participants through the development of their own sample application using Berkeley DB. Audience     Application developers     Software engineers     Technical consultants Format of the course     Part lecture, part discussion, hands-on development and implementation, tests to gauge understanding Introduction Installing Berkeley DB Configuring Berkeley DB Database operations Working with the Berkeley DB API Creating transactional applications in Berkeley DB Creating concurrent data stores Cursor operations Querying the database Working with indexes Replicating your application Berkeley DB utilities Building, configuring and updating Berkeley DB Backup and recovery Tuning Berkeley DB
storm Apache Storm 28 hours Apache Storm is a distributed, real-time computation engine used for enabling real-time business intelligence. It does so by enabling applications to reliably process unbounded streams of data (a.k.a. stream processing). "Storm is for real-time processing what Hadoop is for batch processing!" In this instructor-led live training, participants will learn how to install and configure Apache Storm, then develop and deploy an Apache Storm application for processing big data in real-time. Some of the topics included in this training include: Apache Storm in the context of Hadoop Working with unbounded data Continuous computation Real-time analytics Distributed RPC and ETL processing Request this course now! Audience Software and ETL developers Mainframe professionals Data scientists Big data analysts Hadoop professionals Format of the course     Part lecture, part discussion, exercises and heavy hands-on practice Request a customized course outline for this training!
zeppelin Zeppelin for interactive data analytics 14 hours Apache Zeppelin is a web-based notebook for capturing, exploring, visualizing and sharing Hadoop and Spark based data. This instructor-led, live training introduces the concepts behind interactive data analytics and walks participants through the deployment and usage of Zeppelin in a single-user or multi-user environment. By the end of this training, participants will be able to: Install and configure Zeppelin Develop, organize, execute and share data in a browser-based interface Visualize results without referring to the command line or cluster details Execute and collaborate on long workflows Work with any of a number of plug-in language/data-processing-backends, such as Scala ( with Apache Spark ), Python ( with Apache Spark ), Spark SQL, JDBC, Markdown and Shell. Integrate Zeppelin with Spark, Flink and Map Reduce Secure multi-user instances of Zeppelin with Apache Shiro Audience Data engineers Data analysts Data scientists Software developers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us.  
tidyverse Introduction to Data Visualization with Tidyverse and R 7 hours The Tidyverse is a collection of versatile R packages for cleaning, processing, modeling, and visualizing data. Some of the packages included are: ggplot2, dplyr, tidyr, readr, purrr, and tibble. In this instructor-led, live training, participants will learn how to manipulate and visualize data using the tools included in the Tidyverse. By the end of this training, participants will be able to: Perform data analysis and create appealing visualizations Draw useful conclusions from various datasets of sample data Filter, sort and summarize data to answer exploratory questions Turn processed data into informative line plots, bar plots, histograms Import and filter data from diverse data sources, including Excel, CSV, and SPSS files Audience Beginners to the R language Beginners to data analysis and data visualization Format of the course Part lecture, part discussion, exercises and heavy hands-on practice Introduction     Tydyverse vs traditional R plotting Setting up your working environment Preparing the dataset Importing and filtering data Wrangling the data Visualizing the data (graphs, scatter plots) Grouping and summarizing the data Visualizing the data (line plots, bar plots, histograms, boxplots) Working with non-standard data Closing remarks
meanangular2 Angular 2: Building Web Apps using the MEAN stack 35 hours MEAN stack is a full-stack JavaScript solution that helps you write and deploy scalable, robust, and maintainable web applications quickly and easily using MongoDB, Express, Angular, and Node.js. By the end of this hands-on intensive training course, the students will be able to: Store the data in NoSQL, document-oriented MongoDB database that brings performance and scalability. Use Node.js, the server-side platform built on Google V8’s runtime for building fast, scalable network applications. Use Express, a simple yet powerful web application development HTTP server framework built on top of Node.js. Use Angular 2 framework that offers declarative, two-way data binding for web applications. Take advantage of the ‘full-stack JavaScript’ paradigm i.e. store documents in JSON-like format in MongoDB, author JSON queries in Node.js/Express.js, and forward these JSON documents back to an Angular-based frontend. Get acquainted with the latest web application development trends in the IT industry. Notes: Angular is available in different versions, for example: AngularJS ( a.k.a. Angular.js, AngularJS 1, and Angular 1) Angular 2 Angular 4 etc. This training covers Angular 2. For all other components (Node.js, Express, MongDB) we cover the latest stable version. If you wish to customize the versions taught in this training, please contact us to arrange.   Node.js Getting started with Node.js Node Package Manager Modules Asynchronous Programming Callbacks Events Streams Web Sockets Angular 2 Overview of Typescript Angular Architecture Modules, Controllers and Scope Views Two-way Binding Built-in and Custom Directives Event Directives Expressions Built-in and Custom Filters Understanding the Digest Loop Forms and Validation Angular 2 Service Types Factories, Providers, Decorators, DI Creating Custom Services Consuming Ajax Web Services via $http and $resource Routing, Redirects, and Promises Express.js MVC Pattern Introduction to Express Routing HTTP Interaction Handling Form Data Handling Query Parameters Cookies and Sessions User Authentication Error Handling Creating and Consuming RESTful Services Using Templates MongoDB Understanding NoSQL MongoDB Finding Documents Update, Insert, and Upsert Indexing Data Modeling Aggregation
sqlfun SQL Fundamentals 14 hours This SQL training course is for people who want to gain the necessary skills to extract and analyse data from any database and create reports. Course members will learn: how to write SQL queries what relational databases are and how we can use them what are relations and how to create them the structure of data differences between SQL dialects (Oracle, T-SQL, ANSI) practical skills for writing queries This SQL course deals with generic ANSI SQL. It can be used in any database, including Oracle, MySQL, Microsoft Access, Microsoft SQL Server, DB2, Informix, PostgreSQL any other relational databases. RDBMS (Relational DataBase Management System) Relational Operators SQL as Declarative Language SQL Syntax SQL Sublanguages DQL, DML, DDL, DCL DQL (Data Query Language) in Detail SELECT clause Column aliases Table aliases Date types and Date functions Group function Table joins JOIN clause UNION operator Nested queries Correlated subqueries DML (Data Manipulation Language) Overview Inserting rows (INSERT) Inserting rows using subquery Updating rows (UPDATE) Deleting rows (DELETE) DDL (Data Definition Language) Overview Creating, altering and dropping objects (CREATE, ALTER, DROP) Creating tables using subquery (CREATE TABLE .... AS SELECT...) CONSTRAINTS Overview NULL i NOT NULL CONSTRAINT clause ENUM type SET type PRIMARY KEY UNIQUE FOREIGN KEY DEFAULT clause Transactions Overview COMMIT ROLLBACK SAVEPOINT Implicit and explicit rollbacks and commits SQL Dialects Overview MySQL Microsoft Access and SQL Server Oracle and PostgreSQL
ddavsvbsqls Developing Desktop Applications with Visual Studio 2012, VB.NET and SQL Server 2012 21 hours This course is divided into 3 main sections and is made up of a mixture of presentations and practical exercises. VB.NET Language in Visual Studio 2012 VB.NET Object Orientation VB.NET and Sql Server 2012 Part I. VB.NET Language in Visual Studio 2012 Module 1. Introduction to Visual Basic 2012 The Object-Oriented Programming The Visual Studio 2012 IDE Creating a new Application Using the Help System Module 2. The Microsoft .NET Framework The .NET Framework Classes Executing the Code Common Language Runtime Code Loading and Execution Application Isolation Security Interoperability Exception Handling Module 3. The Visual Basic 2012 Language Data Types Storing Variables Using Methods Making Decisions Working with Data Structures Using Arrays, Enumerations and Collections Module 4. Building Windows Applications Responding to Events Creating the Toolbar Creating the Status Bar Using Multiple Forms OpenFileDialog and SaveDialog controls PrintDialog and FolderBrowserDialog controls Understanding Menu Features Creating Menus Context Menus Part II. VB.NET Object Orientation Module 5. Building Objects Understanding Objects Encapsulation Methods and Properties Managing Events Building Classes Using Constructors Managing Inheritance Module 6. Advanced Language Constructs Using Lambda Expressions Using Async and Wait Using Iterators Module 7. Exception Handling and Debugging Handling Exceptions Try, Catch, Finally The Throw Keyword The Exit Try Statement Using Exit Try Statement Using Exception Properties Logging Errors Module 8. Parallel Programming Using Tasks and Threads Launching Parallel Tasks Transforming Sequential Code to Parallel Code Parallelizing Loops Specifying the Desired Degree of Parallelism Creating and Managing Tasks Part III. VB.NET and Sql Server 2012 Module 9. Database Programming with Sql Server 20012 and ADO.NET The ADO.NET architecture The Connection class The Command and DataReader Classes The ExecuteReader(), ExecuteScalar(), ExecuteNonQuery() methods Using Parameterized Commands Calling Stored Procedure Managing Transactions Module 10. Data Components and the DataSet Building a Data Access Component Managing Disconnected Data The DataSet Class The DataAdapter Class: Filling a DataSet, working with Multiple Tables and Relationships The DataView Class Module 11. Using Data Binding Basic Data Binding Data Source Controls The SqlDataSource Inserting, Updating, Deleting and Selecting records
3419 Oracle 11g - Programming with PL / SQL II 21 hours For who This training is in addition to, and continuation of the 'Oracle 11g - Programming in PL / SQL and - workshops ", but can also be designed for practitioners, developers, PL / SQL who already have experience with the language, and who want to systematize their knowledge and learn advanced mechanisms and solutions developed in this language. The content of the training Objects, streams and complex data structures Advanced solutions based on PL / SQL Exams and Certificates The plan covers the training material required to pass the exam 1Z0-146 Oracle Advanced PL / SQL and obtain the title of Oracle Advanced PL / SQL Developer Certified Professional Purpose of training The training is designed to familiarize participants with the advanced aspects of programming in an Oracle database. The emphasis is on flexibility and performance solutions based on PL / SQL. Notes The workshops are based on the software version 11g XE Complex data types, collections Subtypes Cursor variables and dynamic cursors Associative arrays, collections Actions mass, bulk, forall Exception handling bulk operations Object orientation in an Oracle database Types (classes) methods of objects permanent Collections Functions Panel streaming Features Create your own aggregate functions Calling functions in SQL, constraints, levels of purity, determinism Organization of program units PL / SQL Permissions in PL / SQL Context name Integration with other languages Using JAVA Linking procedures C language Native compilation of the C language Ready solutions Create the application context Mechanism of Virtual Private Database (VPD) Support lobbying Profiling code Tracking code Productivity PL / SQL code Bind variables in SQL statements and the statistical distribution of cursor Sharing Objective query optimization Feather short procedures at compile Caching functions and query results Prevention before injecting code
accumulo Apache Accumulo: Building highly scalable big data applications 21 hours Apache Accumulo is a sorted, distributed key/value store that provides robust, scalable data storage and retrieval. It is based on the design of Google's BigTable and is powered by Apache Hadoop, Apache Zookeeper, and Apache Thrift.   This courses covers the working principles behind Accumulo and walks participants through the development of a sample application on Apache Accumulo. Audience     Application developers     Software engineers     Technical consultants Format of the course     Part lecture, part discussion, hands-on development and implementation, occasional tests to gauge understanding Introduction Installing Accumulo Configuring Accumulo Understanding Accumulo's data model, architecture, and components Working with the shell Database operations Configuring your tables Accumulo iterators Developing an application in Accumulo Securing your application Reading and writing secondary indexes Working with Mapreduce, Spark, and Thrift Proxy Testing your application Troubleshooting Deploying your application Accumulo Administrative tasks
hadoopmapr Hadoop Administration on MapR 28 hours Audience: This course is intended to demystify big data/hadoop technology and to show it is not difficult to understand. Big Data Overview: What is Big Data Why Big Data is gaining popularity Big Data Case Studies Big Data Characteristics Solutions to work on Big Data. Hadoop & Its components: What is Hadoop and what are its components. Hadoop Architecture and its characteristics of Data it can handle /Process. Brief on Hadoop History, companies using it and why they have started using it. Hadoop Frame work & its components- explained in detail. What is HDFS and Reads -Writes to Hadoop Distributed File System. How to Setup Hadoop Cluster in different modes- Stand- alone/Pseudo/Multi Node cluster. (This includes setting up a Hadoop cluster in VirtualBox/KVM/VMware, Network configurations that need to be carefully looked into, running Hadoop Daemons and testing the cluster). What is Map Reduce frame work and how it works. Running Map Reduce jobs on Hadoop cluster. Understanding Replication , Mirroring and Rack awareness in context of Hadoop clusters. Hadoop Cluster Planning: How to plan your hadoop cluster. Understanding hardware-software to plan your hadoop cluster. Understanding workloads and planning cluster to avoid failures and perform optimum. What is MapR and why MapR : Overview of MapR and its architecture. Understanding & working of MapR Control System, MapR Volumes , snapshots & Mirrors. Planning a cluster in context of MapR. Comparison of MapR with other distributions and Apache Hadoop. MapR installation and cluster deployment. Cluster Setup & Administration: Managing services, nodes ,snapshots, mirror volumes and remote clusters. Understanding and managing Nodes. Understanding of Hadoop components, Installing Hadoop components alongside MapR Services. Accessing Data on cluster including via NFS Managing services & nodes. Managing data by using volumes, managing users and groups, managing & assigning roles to nodes, commissioning decommissioning of nodes, cluster administration and performance monitoring, configuring/ analyzing and monitoring metrics to monitor performance, configuring and administering MapR security. Understanding and working with M7- Native storage for MapR tables. Cluster configuration and tuning for optimum performance. Cluster upgrade and integration with other setups: Upgrading software version of MapR and types of upgrade. Configuring Mapr cluster to access HDFS cluster. Setting up MapR cluster on Amazon Elastic Mapreduce. All the above topics include Demonstrations and practice sessions for learners to have hands on experience of the technology.
ApacheIgnite Apache Ignite: Improve speed, scale and availability with in-memory computing 14 hours Apache Ignite is an in-memory computing platform that sits between the application and data layer to improve speed, scale and availability. In this instructor-led, live training, participants will learn the principles behind persistent and pure in-memory storage as they step through the creation of a sample in-memory computing project. By the end of this training, participants will be able to: Use Ignite for in-memory, on-disk persistence as well as a purely distributed in-memory database Achieve persistence without syncing data back to a relational database Use Ignite to carry out SQL and distributed joins Improve performance by moving data closer to the CPU, using RAM as a storage Spread data sets across a cluster to achieve horizontal scalability Integrate Ignite with RDBMS, NoSQL, Hadoop and machine learning processors Audience Developers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us.
mariadbadv Advanced MariaDB for High Availability and Performance 28 hours MariaDB is a fork of MySQL and one of the most popular database servers. In this instructor-led, live training, participants will learn how to install, configure and manage MariaDB for high availability and performance. Other topics include backup and recovery, security and clustering. Audience Developers Database administrators System administrators Format of the course Part lecture, part discussion, exercises and heavy hands-on practice Introduction Installing and configuring MariaDB Overview of MariaDB architecture Backing up and restoring MariaDB Point-in-Time-Recovery (PiTR) Securing MariaDB Configuring MariaDB for high availability Master-slave replication Master-master replication Setting up virtual IPs Read/write distribution Active-active clustering with Galera Cluster Load balancing Performance tuning in MariaDB Hardware and performance Schema tuning Indexing SQL query Tuning Profiling Closing remarks
elasticsearchfordevs ElasticSearch for developers: building search and analytics solutions with Elasticsearch 14 hours Elasticsearch is an open-source, distributed search engine. It is commonly used together with Logstash (data-collection and log-parsing engine) and Kibana (analytics and visualization platform) to make up the the "ELK stack". This training is aimed at software developers who wish to build search and analytics solutions using Elasticsearch The training starts with a discussion of the ElastickSearch architecture, including its distributed model and search API. This is followed by an explanation of ElasticSearch's functionality and how to best integrate it into your own application. Hands-on exercises make up an important part of the training, and give participants a chance to put into practice their knowledge while receiving feedback on their implementation and progress. Audience     Software developers Format of the course      Heavy emphasis on live practice. Most of the concepts are learned through samples, exercises and hands-on development. Introduction to Elasticsearch Writing search queries Performing text analysis Defining mappings Expanding your searches The distributed model Manipulating search results Performing aggregations Handling data relationships Closing remarks
sqlmysqladv SQL Advanced in MySQL 7 hours This course has been created for people already acquainted with SQL. The course introduces you into secrets common to all SQL databases as well as MySQL specific syntax, functions and features. DQL (Data Query Language) Correlation in FROM, WHERE, SELECT and HAVING clauses Correlation and performance Using CASE, IF, COALESCE functions Using variables Casting and converting Dealing with NULL, NULL-safe operators Using regular expression with REGEXP operator Useful MySQL specific group by functions (GROUP_CONCAT, etc.) GROUP BY WITH ROLLUP EXISTS, ALL, ANY Multitable OUTER JOIN Rewriting subqueries as joins DML (Data Modification Language) Multi-row inserts INSERT by SELECT Using subqueries in DML statements Using variables in DML queries Locking tables and rows Updating data in many tables IGNORE clause REPLACE clause DELETE versus TRUNCATE DDL (Data Definition Language) Creating tables with select Temporary tables Stored Procedures Short introduction to MySQL stored procedures
3410 Oracle 11g - Programming with PL / SQL I - Workshops 28 hours For who Workshops are dedicated to developers, end users and administrators, who until now have had no contact with the language PL / SQL, and the need to exploit its huge potential in working with a database, automate processes, and in building applications Exams and Certificates The plan covers the training material required to pass the exam 1Z0-144 Oracle Database 11g Program with PL / SQL and obtain the title of Oracle PL / SQL Developer Certified Associate Purpose of training The workshop aims to familiarize participants with the programming language PL / SQL, its capabilities and limitations. This workshop will include a full understanding of the mechanisms involved in the programming language PL / SQL needed to implement the logic of the free applications, automation of data processing and database management. The content of the training Introduction to PL / SQL architecture solutions based on this language, the organization of the working environment Create scripts and stored program units that operate on data Notes The workshops are based on the software version 11g XE Introduction to PL / SQL Runtime Environment Construction and types of PL / SQL blocks Declaring and using variables Control statements, decisions, loops SQL statements in PL / SQL DML commands DDL and dynamic SQL TCL commands and transactional SELECT Procedures and Functions Create and delete Parameterization Passing parameters by value and reference, nocopy Handling errors and exceptions Create and use cursors Records static cursors Parameterizing cursors Cursor FOR UPDATE Associative arrays Packages The structure of the package: the specification and body Section Initialization and global variables, memory management, an instance of the package Encapsulation, overloading programs, pre-declaration procedures Triggers DML triggers The triggers Drives (INSTEAD OF) The triggers system New features in Oracle 11g triggers Examples of application packages built Writing to a file through UTL_FILE Sending e-mails Management code and compiler Encryption code (dynamic obfuscation, wrap) conditional Compilation The relationships between objects Warnings
sqlmsa SQL in Microsoft Access 14 hours This SQL training course is for people who want to gain the necessary skills to extract and analyse data using Microsoft Access. Course members will learn: how to write SQL queries what relational databases are and how we can use them what are relations and how to create them the structure of data differences between SQL dialects (Oracle, T-SQL, ANSI) practical skills for writing queries This SQL course deals with Microsoft Access dialect of SQL. RDBMS (Relational DataBase Management System) Relational Operators SQL as Declarative Language SQL Syntax SQL Sublanguages DQL, DML, DDL, DCL DQL (Data Query Language) in Detail SELECT clause Column aliases Table aliases Date types and Date functions Group function Table joins JOIN clause UNION operator Nested queries Correlated subqueries DML (Data Manipulation Language) Overview Inserting rows (INSERT) Inserting rows using subquery Updating rows (UPDATE) Deleting rows (DELETE) DDL (Data Definition Language) Overview Creating, altering and dropping objects (CREATE, ALTER, DROP) Creating tables using subquery (CREATE TABLE .... AS SELECT...) CONSTRAINTS Overview NULL i NOT NULL CONSTRAINT clause ENUM type SET type PRIMARY KEY UNIQUE FOREIGN KEY DEFAULT clause Transactions Overview COMMIT ROLLBACK SAVEPOINT Implicit and explicit rollbacks and commits SQL Dialects Overview MySQL Microsoft Access and SQL Server Oracle and PostgreSQL
bigddbsysfun Big Data & Database Systems Fundamentals 14 hours The course is part of the Data Scientist skill set (Domain: Data and Technology). Data Warehousing Concepts What is Data Ware House? Difference between OLTP and Data Ware Housing Data Acquisition Data Extraction Data Transformation. Data Loading Data Marts Dependent vs Independent data Mart Data Base design ETL Testing Concepts: Introduction. Software development life cycle. Testing methodologies. ETL Testing Work Flow Process. ETL Testing Responsibilities in Data stage.       Big data Fundamentals Big Data and its role in the corporate world The phases of development of a Big Data strategy within a corporation Explain the rationale underlying a holistic approach to Big Data Components needed in a Big Data Platform Big data storage solution Limits of Traditional Technologies Overview of database types NoSQL Databases Hadoop Map Reduce Apache Spark
datameer Datameer for Data Analysts 14 hours Datameer is a business intelligence and analytics platform built on Hadoop. It allows end-users to access, explore and correlate large-scale, structured, semi-structured and unstructured data in an easy-to-use fashion. In this instructor-led, live training, participants will learn how to use Datameer to overcome Hadoop's steep learning curve as they step through the setup and analysis of a series of big data sources. By the end of this training, participants will be able to: Create, curate, and interactively explore an enterprise data lake Access business intelligence data warehouses, transactional databases and other analytic stores Use a spreadsheet user-interface to design end-to-end data processing pipelines Access pre-built functions to explore complex data relationships Use drag-and-drop wizards to visualize data and create dashboards Use tables, charts, graphs, and maps to analyze query results Audience Data analysts Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us.
datastorageoverview Which data storage to choose - from flat files, through SQL, NoSQL to massive distributed systems 7 hours This course helps customer to chose the write data storage depend on their needs. It covers almost all possible modern approaches. File Document Storage (Cloud Storage) Features (OCR, Scalaibility, Search, etc...) Open Source examples (e.g. Next Cloud) Some commercial examples Flat file storage XML databases CSV databases Relational databases Normalization Dependencies and Constrants Scalability - replications, clusters Open Source and commercial software (MySQL, PostrgreSQL, DM7, Oracle, etc..) NoSQL Storage Document Oriented Databases (MongoDB, CouchDB etc...) Column Orientation (Canadra, Scylla etc...) Search Orientation (Elasticsearch... NewSQL CAP Theorem Opensource software (SequoiaDB, etc...) Search Engines Features (text processing, relevancy, etc...) Open Source examples Scalability, High Availability, Load Balacing, etc.... Traditional Datawherehouses Business Inteligence, OLTP and Datawherehouse Opensource and commercial solutions MapReduce and Distributed Parallel Processing Hadoop-like (Hive, HFS, Impala) Distributed filesystem Overview of opensource (Ceph etc...) In-memory Databases Opensource solution (e.g. ApacheIgnite) Others Hypertable (Google Bigtable) BigQuery AWS solutsion (S3, etc...) Beyond present - future trends
matlabdsandreporting MATLAB Fundamentals, Data Science & Report Generation 126 hours In the first part of this training, we cover the fundamentals of MATLAB and its function as both a language and a platform.  Included in this discussion is an introduction to MATLAB syntax, arrays and matrices, data visualization, script development, and object-oriented principles. In the second part, we demonstrate how to use MATLAB for data mining, machine learning and predictive analytics. To provide participants with a clear and practical perspective of MATLAB's approach and power, we draw comparisons between using MATLAB and using other tools such as spreadsheets, C, C++, and Visual Basic. In the third part of the training, participants learn how to streamline their work by automating their data processing and report generation. Throughout the course, participants will put into practice the ideas learned through hands-on exercises in a lab environment. By the end of the training, participants will have a thorough grasp of MATLAB's capabilities and will be able to employ it for solving real-world data science problems as well as for streamlining their work through automation. Assessments will be conducted throughout the course to gauge progress. Format of the course Course includes theoretical and practical exercises, including case discussions, sample code inspection, and hands-on implementation. Note Practice sessions will be based on pre-arranged sample data report templates. If you have specific requirements, please contact us to arrange. Introduction MATLAB for data science and reporting   Part 01: MATLAB fundamentals Overview     MATLAB for data analysis, visualization, modeling, and programming. Working with the MATLAB user interface Overview of MATLAB syntax Entering commands     Using the command line interface Creating variables     Numeric vs character data Analyzing vectors and matrices     Creating and manipulating     Performing calculations Visualizing vector and matrix data Working with data files     Importing data from Excel spreadsheets Working with data types     Working with table data Automating commands with scripts     Creating and running scripts     Organizing and publishing your scripts Writing programs with branching and loops     User interaction and flow control Writing functions     Creating and calling functions     Debugging with MATLAB Editor Applying object-oriented programming principles to your programs   Part 02: MATLAB for data science Overview     MATLAB for data mining, machine learning and predictive analytics Accessing data     Obtaining data from files, spreadsheets, and databases     Obtaining data from test equipment and hardware     Obtaining data from software and the Web Exploring data     Identifying trends, testing hypotheses, and estimating uncertainty Creating customized algorithms Creating visualizations Creating models Publishing customized reports Sharing analysis tools     As MATLAB code     As standalone desktop or Web applications Using the Statistics and Machine Learning Toolbox Using the Neural Network Toolbox   Part 03: Report generation Overview     Presenting results from MATLAB programs, applications, and sample data     Generating Microsoft Word, PowerPoint®, PDF, and HTML reports.     Templated reports     Tailor-made reports         Using organization’s templates and standards Creating reports interactively vs programmatically     Using the Report Explorer     Using the DOM (Document Object Model) API Creating reports interactively using Report Explorer     Report Explorer Examples         Magic Squares Report Explorer Example     Creating reports         Using Report Explorer to create report setup file, define report structure and content     Formatting reports         Specifying default report style and format for Report Explorer reports     Generating reports         Configuring Report Explorer for processing and running report     Managing report conversion templates         Copying and managing Microsoft Word , PDF, and HTML conversion templates for Report Explorer reports     Customizing Report Conversion templates         Customizing the style and format of Microsoft Word and HTML conversion templates for Report Explorer reports     Customizing components and style sheets         Customizing report components, define layout style sheets Creating reports programmatically in MATLAB     Template-Based Report Object (DOM) API Examples         Functional report         Object-oriented report         Programmatic report formatting     Creating report content         Using the Document Object Model (DOM) API     Report format basics         Specifying format for report content     Creating form-based reports         Using the DOM API to fill in the blanks in a report form     Creating object-oriented reports         Deriving classes to simplify report creation and maintenance     Creating and formatting report objects         Lists, tables, and images     Creating DOM Reports from HTML         Appending HTML string or file to a Microsoft® Word, PDF, or HTML report generated by Document Object Model (DOM) API     Creating report templates         Creating templates to use with programmatic reports     Formatting page layouts         Formatting pages in Microsoft Word and PDF reports Summary and closing remarks
mysqladm MySQL Database Administration 14 hours MySQL Administration training course is for anyone who wants to administrate the MySQL database server. It is a comprehensive course covering all administrator duties. The course explains how MySQL Database works, what tools are available, how we can use them, how we can secure the MySQL Database Server and configure it. During the training course you will learn how to manage user accounts and how the MySQL Access Privilege System works. You also will learn how to maintain your database, backup and recover your databases and perform crash recovery. MySQL Server Files and Scripts MySQL Programs MySQL Server MySQL Client GUI Tools MySQL Server Configuration mysqld Options The Server SQL Mode Server System Variables Dynamic System Variables Server Status Variables Shutdown Process MySQL Security Issues Securing MySQL Against Attacks Security-Related mysqld Options Security Issues with LOAD DATA LOCAL MySQL Access Privilege System MySQL Privilege System Overview Privileges Provided by MySQL Connecting to the MySQL Server - Stages Access Control, Stage 1: Connection Verification Access Control, Stage 2: Request Verification Access Denied Errors MySQL User Account Management Users and Passwords Creating New Users Deleting User Accounts Limiting User Resources Changing Passwords MySQL Database Maintenance Backup and Recovery Point-in-Time Recovery Maintenance and Crash Recovery myisamchk Syntax and Options Getting Table Information MySQL Local Setting National Characters and Sorting MySQL Server Time Zone MySQL Log Files Error Log General Query Log Update Log Binary Log Slow Query Log Log File Maintenance and Rotation Running Multiple MySQL Servers on the Same Machine Running Multiple Servers in Windows Running Multiple Servers in Windows as Services Running Multiple Servers in Unix and Linux Using Client Tools in a Multi-Server Environment MySQL Query Cache The Concept of Query Cache Testing Query Cache with SELECT Configuring Query Cache Checking Query Cache Status and Maintenance
3358 Oracle 11g - SQL language for developers - Workshop 35 hours For who Workshops are dedicated as a first step for developers and designers of applications based on Oracle databases. Participants do not need to have any prior knowledge of the Oracle database, or other relational database systems, even though such knowledge may be useful. Exams and Certificates The plan covers the training material required to pass the exam 1Z0-047 Oracle Database SQL Expert and obtain the title of Oracle Database SQL Certified Expert Purpose of training The workshop aims to familiarize participants with the Oracle database techniques to build database structures and data manipulation. Particular emphasis is placed on the participant to see across the board, which offers opportunities to design and build applications Relational Database Management System, Oracle Database, and to be able to independently work with her. The content of the training Introduction to database technology and the organization of the work environment Acquisition and modification of data Construction of the repository application Safety and concurrency runtime Notes The workshops are based on the software version 11g XE Introduction to the Oracle database Database Architecture Relational model database Users diagrams sessions Tools Introduction to the SELECT statement Screening and selection (WHERE clause) Sorting Data types, operators, and service NULL Built-in scalar functions Actions to date National and regional settings in SQL The analysis of aggregated data Funkcje grupujące Klauzula distinct Klauzule GROUP BY and having Retrieving data from multiple tables Inner and outer joins (INNER JOIN, OUTER JOIN) ANSI SQL syntax, and other methods connectors (SELF JOIN, NATURAL JOIN) Collective operators (UNION, UNION ALL, INTERSECT, MINUS) Subqueries Subqueries simple Correlated subqueries Operators EXISTS and NOT EXISTS Other types of subqueries Inquiries hierarchical and samples Construction of the tree (CONNECT BY PRIOR clause and START WITH) The SYS_CONNECT_BY_PATH Data samples (SAMPLE clause) Data manipulation (DML) "INSTRUCCIONES INSERT, UPDATE, DELETE Operacja na dużych zbiorach (INSERT FIRST, ALL INSERT, MERGE) Dictionary system Concurrent users work Transactions Locks FLASHBACK Users and Permissions Creating and modifying user patterns Permissions and roles Managing data storage - logical layer Tables, temporary tables, index-organized tables Limitations Indexes The views, sequences, synonyms, materialized views Units stored PL / SQL Modeling and restore the data model using Oracle SQL Modeler Moving Data A logical copy of the data - datapump import and export Loading data - sqlLoader External tables Links database Automating tasks dbms_jobs, dbms_scheduler
mariadbgc MariaDB Galera Cluster Administration 21 hours This course is intended for database administrators. The course presents options for High-Availability solutions using Galera Cluster. You will learn the basics of Galera technology, as well as more advanced topics and practical knowledge related to configuring, optimizing and administering a Galera Cluster. Topic overview Why I need them and what are High-Availability solutions? Cluster concepts ​What is MariaDB Galera Cluster and what it offers to my organization? Galera Cluster Management How to start with Galera - what should I now before installation? Architecture and functionality First steps - Installation Going deeper - Configuration and Set-up Almost like a pro - Administration Performance Operations and operation modes Upgrade Galera Backups and restoring ​Controlling state transfer between nodes Load balancing Monitoring How to deal with Galera multi- master configuration Advanced features Security Scalability Replication ​Advanced configuration
hivehiveql Data Analysis with Hive/HiveQL 7 hours This course covers how to use Hive SQL language (AKA: Hive HQL, SQL on Hive, HiveQL) for people who extract data from Hive Hive Overview Architecture and design Aata types SQL support in Hive Creating Hive tables and querying Partitions Joins Text processing labs : various labs on processing data with Hive DQL (Data Query Language) in Detail SELECT clause Column aliases Table aliases Date types and Date functions Group function Table joins JOIN clause UNION operator Nested queries Correlated subqueries
redisadev Redis for Developers and System Administrators 14 hours Redis is an open source (BSD licensed), in-memory data structure store, used as database, cache and message broker.Day 1: developer topics Redis Releases Installation Configuration Starting Redis Redis client libraries and language bindings Redis data types and commands to manipulate them Strings List, Sets & Sorted sets Hashes Bit arrays HyperLogLogs Redis Pub/Sub Expiration Redis transactions & Lua scripts Performance tips Benchmarking Redis Commands to avoid Pipelining Memory optimization Mass insertion Day 2: advanced usage and sysadmin topics Partitioning Data organization tips Distributed locks Master-slave replication Redis Cluster Persistence Security Starting multiple instances of Redis Connection limits, timeouts & other safeguards High availability Latency monitoring
cassdev Cassandra for Developers 21 hours This course will introduce Cassandra –  a popular NoSQL database.  It will cover Cassandra principles, architecture and data model.   Students will learn data modeling  in CQL (Cassandra Query Language) in hands-on, interactive labs.  This session also discusses Cassandra internals and some admin topics. Audience : Developers Section 1: Introduction to Big Data / NoSQL NoSQL overview CAP theorem When is NoSQL appropriate Columnar storage NoSQL ecosystem Section 2 : Cassandra Basics Design and architecture Cassandra nodes, clusters, datacenters Keyspaces, tables, rows and columns Partitioning, replication, tokens Quorum and consistency levels Labs : interacting with cassandra using CQLSH Section 3: Data Modeling – part 1 introduction to CQL CQL Datatypes creating keyspaces & tables Choosing columns and types Choosing primary keys Data layout for rows and columns Time to live (TTL) Querying with CQL CQL updates Collections (list / map / set) Labs : various data modeling exercises using CQL ; experimenting with queries and supported data types Section 4: Data Modeling – part 2 Creating and using secondary indexes composite keys (partition keys and clustering keys) Time series data Best practices for time series data Counters Lightweight transactions (LWT) Labs : creating and using indexes;  modeling time series data Section 5 : Data Modeling Labs  : Group design session multiple use cases from various domains are presented students work in groups to come up designs and models discuss various designs, analyze decisions Lab : implement one of the scenario Section 6: Cassandra drivers Introduction to Java driver CRUD (Create / Read / Update, Delete) operations using Java client Asynchronous queries Labs : using Java API for Cassandra Section 7 : Cassandra Internals understand Cassandra design under the hood sstables, memtables, commit log read path / write path caching vnodes Section 8: Administration Hardware selection Cassandra distributions Cassandra best practices (compaction, garbage collection,) troubleshooting tools and tips Lab : students install Cassandra, run benchmarks Section 9:  Bonus Lab (time permitting) Implement a music service like Pandora / Spotify on Cassandra
teraintro Teradata Fundamentals 21 hours Teradata is one of the popular Relational Database Management System. It is mainly suitable for building large scale data warehousing applications. Teradata achieves this by the concept of parallelism.  This course introduces the delegates to Teradata Introduction to Teradata Background Why use Teradata User Scalability Relational Concepts Introduction to RDBMS  Warehousing Concepts Set Up and Installation Installation Tools and Utilities like BTEQ Teradata Architecture Components Node Parsing Engine Message Parsing Layer - BYNET Access Module Processor Storage Architecture Retrieval Architecture Architectural Overview Teradata Basic Concepts - SQL Data Type Tables Permanent Volatile Global Temporary Derived Set v/s Multiset Tables Playing with Data - CRUD Operations [DDL and DML] Logical and Conditional Operators SET Operators String Manipulation Date/Time Built in and Aggregate Functions Joins and Subqueries Indexes Primary Secondary Teradata Advanced Concepts Case Coalesce Macros Stored Procedures Space Temp Spool Permanent Join Strategies Statistics Compression Hashing Algorithm OLAP Functions User Management Teradata Additional Concepts Utilities FastLoad MultiLoad FastExport BTEQ Data Protection Methodologies Optimization Strategies Note: The Training would be a mix of theory and handson, and it would be helpful if the delegates actively particpate in the given exercises.
mongodbadmin MongoDB for Administrators 14 hours This course covers everything a database administrator needs to know to successfully deploy and maintain MongoDB databases. Diagnosing performance issues, importing and exporting data, and establishing the proper backup and restore routines, overview of the MongoDB CRUD API, the command shell, and the drivers. are also covered. The audience of this course include people who want to: Understand MongoDB from a developer's perspective, including its command shell, query API, and driver tools. Deploy MongoDB in all its configurations - as a single server, with master/slave replication, as a replica set, and as a sharded cluster. Evaluate applications and choose hardware appropriately. Monitor MongoDB instances and integrate with standard monitoring software (Munin, Nagios, etc.) Plan for backups and manage large data imports and exports. Troubleshoot the most common developer issues and failure scenarios. Each delegate will need to perform a series of practical exercises. MongoDB Architectural Overview Origin, design goals, key features Process structure (mongos, mongod, config servers) Directory / file structure Working with the MongoDB Shell Documents and data types CRUD (Inserts, queries, updates, deletes) System commands Single-server Configuration and Deployment Configuration files Data files and allocation Log files Hardware and file-system recommendations Security Built-in authentication Recommendations for secure deployment Monitoring MongoDB mongostat Analyzing memory and IO performance Integration with monitoring tools: Munin / Cacti / Nagios MongoDB's web console Indexing and Query Optimization Managing indexes and MongoDB indexing internals Single / Compound / Geo indexes Identifying sub-optimal queries. Using the query profiler. Introduction to drivers (Java/Python/Ruby/PHP/Perl) How the drivers and shell communicate with MongoDB BSON and the MongoDB Wire Protocol Troubleshooting application connections Intro to Read and Write scalability Replication and Durability Master-slave replication Replica sets Using write concern for durability Handling replication failures Auto-Sharding How sharding works Setting up a MongoDB shard cluster Choosing a shard key Sharding and indexes Sharding and Replica Set Topologies Administering a sharded cluster Shard / Chunk Migration Backup and Restore Plans Filesystem-based strategies mongodump / mongorestore rsync mongoimport / mongoexport
sqlmysql SQL in MySQL 14 hours How to build a query? What opportunities has the SQL in a MySQL database? What is a relational database? What is the structure and SQL commands? Relational database models Relational operators Characteristics of declarative SQL language SQL syntax Division language DQL, DML, DDL, DCL Data Query Language SELECT queries. Aliases columns of tables Service date (DATE types, display functions, formatting) Group Features Combining internal and external tables (JOIN clause) UNION operator Nested Subqueries (the WHERE clause, the table name, column name) Correlated subqueries Data Modification Language Inserting rows (INSERT clause) Inserting rows by request Variation of the rows (UPDATE) Delete rows (DELETE) Data Definition Language Creating, altering and dropping objects (CREATE, ALTER, DROP) Creating tables using subquery (CREATE TABLE .... AS SELECT...) CONSTRAINTS Options NULL and NOT NULL CONSTRAINT clause ENUM type type SET PRIMARY KEY condition UNIQUE condition FOREIGN KEY condition DEFAULT clause Transactions The command COMMIT, ROLLBACK, SAVEPOINT
3331 Oracle 11g - Advanced data analysis - workshops 35 hours For who These workshops are a continuation and complement the training of Oracle 11g data-analysis - a workshop dedicated to end users, data analysts and software testers for execution of professional duties which require more advanced techniques for working with the database. As in the case of the training of Oracle 11g data-analysis - workshops, participants do not need to be computer scientists, but the people who need efficient, and above all efficiently use the Oracle database, processing and analyzing stored in the large amounts of data Purpose of training The workshop aims to broaden the knowledge of participants about programming using PL / SQL and issues related to the optimization commands. Particular emphasis in this training is the performance of the data collection to ensure a smooth operation for very large amounts of data. In addition, workshops supplement an understanding of the elements necessary to any advanced user of Oracle in their daily work, such as copying and downloading large amounts of information, data modeling, modification of an existing data model and reverse engineering techniques using Oracle tools. The content of the training Moving and loading Procedural language PL / SQL allows you to expand the analytical capabilities of a SELECT statement Improving the performance of SQL queries Data modeling and acquisition and modification of the existing data model based on Oracle SQL Modeler Notes The workshops are based on the software version 11g XE Managing the data repository Control repository using the system dictionary, SQL script generation Creating tables and relationships with SQL Modeler Play schemes tables and relationships using reverse engineering and SQL Modeler Other repository objects: views, sequences, synonyms, temporary tables, stored routines System privileges and object-oriented database roles The programming language PL / SQL Basic information about the language, data types, variables, Deciding loops Embedding SQL statements in the code PL / SQL Stored subprograms: procedures and functions Handling errors and exceptions Query processing (cursors) The mass data operations (processing array) Generators data streaming functions Permissions in PL / SQL depending on model Triggers Running tasks The task scheduler Powerful scheduling mechanism (SCHEDULER) Methods for data transfer and charging Links database Loading data from text files external Tables Import / Export Data Database performance and tuning SQL statements Architecture database and instance Analysis of the plan to run a command to read the estimated costs and the actual Operation and control of Oracle optimizer with hints (hintów) The use of statistics and histograms Indexing data Optimize index readings Optimizing joins, sorts, and aggregation
nlpwithr NLP: Natural Language Processing with R 21 hours It is estimated that unstructured data accounts for more than 90 percent of all data, much of it in the form of text. Blog posts, tweets, social media, and other digital publications continuously add to this growing body of data. This course centers around extracting insights and meaning from this data. Utilizing the R Language and Natural Language Processing (NLP) libraries, we combine concepts and techniques from computer science, artificial intelligence, and computational linguistics to algorithmically understand the meaning behind text data. Data samples are available in various languages per customer requirements. By the end of this training participants will be able to prepare data sets (large and small) from disparate sources, then apply the right algorithms to analyze and report on its significance. Audience     Linguists and programmers Format of the course     Part lecture, part discussion, heavy hands-on practice, occasional tests to gauge understanding Introduction     NLP and R vs Python Installing and configuring R Studio Installing R packages related to Natural Language Processing (NLP). An overview of R’s text manipulation capabilities Getting started with an NLP project in R Reading and importing data files into R Text manipulation with R Document clustering in R Parts of speech tagging in R Sentence parsing in R Working with regular expressions in R Named-entity recognition in R Topic modeling in R Text classification in R Working with very large data sets Visualizing your results Optimization Integrating R with other languages (Java, Python, etc.) Closing remarks
mssql2016 MS SQL Server 2016 14 hours Performanace and Management Enhanced Database Caching Query data store In-Memory OLTP in SQL Server 2016 Development Temporal Database Temporary Table and Variable Table in-memory Native JSON High Availability and Security Enhanced AlwaysOn Always Enrypted Row-level Security Dynamic Data Masking Data Insight and Business Intelligence Operational Analytics New functionality Columnstore Index Direct Query in SSAS Tabular R Integration (language R in SQL Server) Enhanced SSIS Enhanced MDS Reporting Services New Report Server Mobil Reports SQL Server Mobile Report Publisher Cloud and Hybrid Stretch Database Enhanced backup to Azure Migration SQL Server to Azure SSIS and Data Factory
deckgl deck.gl: Visualizing Large-scale Geospatial Data 14 hours deck.gl is an open-source, WebGL-powered library for exploring and visualizing data assets at scale. Created by Uber, it is especially useful for gaining insights from geospatial data sources, such as data on maps. This instructor-led, live training introduces the concepts and functionality behind deck.gl and walks participants through the set up of a demonstration project. By the end of this training, participants will be able to: Take data from very large collections and turn it into compelling visual representations Visualize data collected from transportation and journey-related use cases, such as pick-up and drop-off experiences, network traffic, etc. Apply layering techniques to geospatial data to depict changes in data over time Integrate deck.gl with React (for Reactive programming) and Mapbox GL (for visualizations on Mapbox based maps). Understand and explore other use cases for deck.gl, including visualizing points collected from a 3D indoor scan, visualizing machine learning models in order to optimize their algorithms, etc. Audience Developers Data scientists Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us.
kdd Knowledge Discover in Databases (KDD) 21 hours Knowledge discovery in databases (KDD) is the process of discovering useful knowledge from a collection of data. Real-life applications for this data mining technique include marketing, fraud detection, telecommunication and manufacturing. In this course, we introduce the processes involved in KDD and carry out a series of exercises to practice the implementation of those processes. Audience     Data analysts or anyone interested in learning how to interpret data to solve problems Format of the course     After a theoretical discussion of KDD, the instructor will present real-life cases which call for the application of KDD to solve a problem. Participants will prepare, select and cleanse sample data sets and use their prior knowledge about the data to propose solutions based on the results of their observations. Introduction     KDD vs data mining Establishing the application domain Establishing relevant prior knowledge Understanding the goal of the investigation Creating a target data set Data cleaning and preprocessing Data reduction and projection Choosing the data mining task Choosing the data mining algorithms Interpreting the mined patterns
ApHadm1 Apache Hadoop: Manipulation and Transformation of Data Performance 21 hours This course is intended for developers, architects, data scientists or any profile that requires access to data either intensively or on a regular basis. The major focus of the course is data manipulation and transformation. Among the tools in the Hadoop ecosystem this course includes the use of Pig and Hive both of which are heavily used for data transformation and manipulation. This training also addresses performance metrics and performance optimisation. The course is entirely hands on and is punctuated by presentations of the theoretical aspects. 1.1Hadoop Concepts 1.1.1HDFS The Design of HDFS Command line interface Hadoop File System 1.1.2Clusters Anatomy of a cluster Mater Node / Slave node Name Node / Data Node 1.2Data Manipulation 1.2.1MapReduce detailed Map phase Reduce phase Shuffle 1.2.2Analytics with Map Reduce Group-By with MapReduce Frequency distributions and sorting with MapReduce Plotting results (GNU Plot) Histograms with MapReduce Scatter plots with MapReduce Parsing complex datasets Counting with MapReduce and Combiners Build reports   1.2.3Data Cleansing Document Cleaning Fuzzy string search Record linkage / data deduplication Transform and sort event dates Validate source reliability Trim Outliers 1.2.4Extracting and Transforming Data Transforming logs Using Apache Pig to filter Using Apache Pig to sort Using Apache Pig to sessionize 1.2.5Advanced Joins Joining data in the Mapper using MapReduce Joining data using Apache Pig replicated join Joining sorted data using Apache Pig merge join Joining skewed data using Apache Pig skewed join Using a map-side join in Apache Hive Using optimized full outer joins in Apache Hive Joining data using an external key value store 1.3Performance Diagnosis and Optimization Techniques Map Investigating spikes in input data Identifying map-side data skew problems Map task throughput Small files Unsplittable files Reduce Too few or too many reducers Reduce-side data skew problems Reduce tasks throughput Slow shuffle and sort Competing jobs and scheduler throttling Stack dumps & unoptimized code Hardware failures CPU contention Tasks Extracting and visualizing task execution times Profiling your map and reduce tasks Avoid the reducer Filter and project Using the combiner Fast sorting with comparators Collecting skewed data Reduce skew mitigation
mongodbdev MongoDB for Developers 14 hours This course covers everything a database developer needs to know to successfully develop applications using MongoDB. Manipulating Documents Query Insert Update Remove Upsert Removing databases, fields and others Document Structure Datatypes References ID Keys Embedded sub-documents Tree structures Tailable Cursor Two Phase Commits Auto-incrementing Sequence field Aggregation  Distinct Aggregation Pipelines Map-reduce Indexes Default _id Single Field Compound Index Multikey Index Geospatial Index Hashed Index Unique Sparse
3041 Access Advanced 21 hours The course participants will learn how to speed up the operation of the database, how to write advanced queries, create a convenient system of forms and reporting. The course introduces the participant to automate all operations using macros and VBA. Tables and Fields Indexes and their usage Validation rules in tables Lists of values Search field Creating and Using OLE Object data type Queries Queries with Union operator Crosstab queries Logical, date, text, convert, aggregate functions Finding duplicates and unmatched records Forms Creating subforms Viewing Totals Opening subforms in a new window Setting the default values for controls Changing form views Reporting Records numbering in groups Creating a multi-column reports Creating report templates Creating user "labels" Charts Creating Charts Embedding charts in forms and reports Editing and modifying charts Macros Creating simple macro Macros Wizard Adding conditions Assigning macros to control events Ways to run macros Creating a macro group Autoexec macro AutoKeys macro Testing macro in the "single step mode" Switchboard Manager   Export and import data Exporting tables and queries Exporting reports as a snapshot Exporting reports to Microsoft Word Importing data from other databases Importing text files (CSV) Importing Excel spreadsheets Linking tables from other databases Database Relational Model and the Database Integrity Foreign keys and ways to maintain consistency Cascade deletion and updating related records Ways to join tables Joining internal, external right and left Joining tables without the clause "join" Testing integrity Tools and Maintenance of the database. Compacting and repairing database Backing up and restoring Database Documenter Database Replication Synchronization Viewing dependencies between objects Smart tags Startup options
3319 Data Analysis with Oracle 11g - workshop 35 hours For who Workshops are dedicated to end users, data analysts and software testers. Workshop participants do not need to be computer scientists, but employees who need efficiently and effectively use the Oracle database, processing and analyzing information contained in it Exams and Certificates The training plan includes, among others material required to pass the exam: 1Z0-051 Oracle Database 11g: SQL Fundamentals I, the first step to getting most certifications Oracle's Database Purpose of training The training is designed to familiarize participants with the Oracle database, the basic tools and techniques of data collection. Particular emphasis in this training is the acquisition of substantially correct and reliable data. The content of the training The organization of the working environment Introduction to the relational model of data storage Techniques for the collection, analysis and synthesis of information stored in the database Modify the information stored in the database Note The workshops are based on the software version 11g XE Introduction to the Oracle database Database Architecture Relational model database Users diagrams sessions Tools Introduction to the SELECT statement Screening and selection (WHERE clause) sorting Data types, operators, and service NULL Built-in scalar functions Actions to date National and regional settings in SQL Regular expressions The analysis of aggregated data grouping Functions DISTINCT clause The GROUP BY clause and HAVING. Summary (clauses ROLLUP, CUBE, GROUPING) Retrieving data from multiple tables Inner and outer joins (INNER JOIN, OUTER JOIN) ANSI SQL syntax, and other methods connectors (SELF JOIN, NATURAL JOIN) Collective operators (UNION, UNION ALL, INTERSECT, MINUS) Subqueries Subqueries simple Correlated subqueries Operators EXISTS and NOT EXISTS Other types of subqueries Inquiries hierarchical and samples Construction of the tree (CONNECT BY PRIOR clause and START WITH) The SYS_CONNECT_BY_PATH Data samples (SAMPLE clause) Analytic Functions Generating summaries Definition window Statistical Functions New features in Oracle 11g Inquiries Pivot (PIVOT, UNPIVOT) Tables and referential integrity Managing tables (CREATE, ALTER, DROP, RENAME) Referential integrity (constraints) Data manipulation (DML) INSTRUCCIONES INSERT, UPDATE, DELETE Operacja na dużych zbiorach (INSERT FIRST, ALL INSERT, MERGE) Concurrent users work Transactions Locks FLASHBACK Brief overview of schema objects vistas sequences indexes
cassdbfun Fundamentals of Cassandra DB 21 hours This course introduces the basics of Cassandra 2.0 including its installation & configuration, internal architecture, tools, Cassandra Query Language, and administration. Audience Administrators and developers seeking to use Cassandra. This course serves as a foundation and prerequisite for other advanced Cassandra courses.   Introduction to Cassandra Big Data Common use cases of Cassandra Cassandra architecture Installation and Configuration Running and Stopping Cassandra instance Cassandra Data Model Cassandra Query Language Configuring the Cassandra nodes and clusters using CCM cqlsh shell commands nodetool Using cassandra-stress to populate and test the Cassandra nodes Coordinating the Cassandra requests Replication Consistency Tuning Cassandra Nodes Communication Writing and Reading data to/from the storage engine Data directories Anti-entropy operations Cassandra Compaction Choosing and Implementing compaction strategies Best practices in hardware planning Troubleshooting resources
postgresadmin PostgreSQL for Administrators 14 hours This course covers the administration and performance tuning of PostgreSQL databases.  Target audience includes system administrators and database architects. Attendees will learn the use of specialised PostgreSQL (AKA Postgres) modules such as replication, connection pooling and full text searching. What is PostgreSQL? A Brief History of PostgreSQL Conventions Further Information Bug Reporting Guidelines Introduction to PostgreSQL Installation and Creating Database The SQL Language Advanced Features The SQL Language SQL Syntax Data Definition Data Manipulation Queries Data Types Functions and Operators Foreign Data Wrappers Type Conversion Indexes Triggers Full Text Search The Information Schema PL/pgSQL - SQL Procedural Language Concurrency Control Performance Tips How the Planner Uses Statistics Server Administration Source Code vs Distribution-Provided Packages Installation from Source Code Installation from Source Code on Windows Deployment of Binaries Obtained by Compiling Source Code Server Setup, Operation Database Physical Storage Filesystem Durability Requirements and Required Mount Options Server Configuration Special Considerations for Container-Based Deployments Client Authentication Database Roles Managing Databases Localization Routine Database Maintenance Tasks Backup and Restore Recovery Configuration Monitoring Database Activity Monitoring Disk Usage Reliability and the Write-Ahead Log Regression Tests Installation of Third-Party Server Extensions High Availability, Load Balancing, and Replication Brewer's CAP Theorem Synchronous vs Asynchronous Replication Log Shipping (Warm Standby) Streaming Master-Slave Replication (Hot Standby) Trigger-Based Master-Slave Replication with Slony Trigger-Based Multi-Master Replication with Bucardo Connection Pooling and Synchronous Replication with Pgpool Failover Configurations using DRBD Replacing a Failed Server Recovering from Network Partition
embeddingprojector Embedding Projector: Visualizing your Training Data 14 hours Embedding Projector is an open-source web application for visualizing the data used to train machine learning systems. Created by Google, it is part of TensorFlow. This instructor-led, live training introduces the concepts behind Embedding Projector and walks participants through the setup of a demo project. By the end of this training, participants will be able to: Explore how data is being interpreted by machine learning models Navigate through 3D and 2D views of data to understand how a machine learning algorithm interprets it Understand the concepts behind Embeddings and their role in representing mathematical vectors for images, words and numerals. Explore the properties of a specific embedding to understand the behavior of a model Apply Embedding Project to real-world use cases such building a song recommendation system for music lovers Audience Developers Data scientists Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us.
scylladb Scylla database 21 hours Scylla is an open-source distributed NoSQL data store. It is compatible with Apache Cassandra but performs at significantly higher throughputs and lower latencies. In this course, participants will learn about Scylla's features and architecture while obtaining practical experience with setting up, administering, monitoring, and troubleshooting Scylla.   Audience     Database administrators     Developers     System Engineers Format of the course     The course is interactive and includes discussions of the principles and approaches for deploying and managing Scylla distributed databases and clusters. The course includes a heavy component of hands-on exercises and practice. Introduction to Scylla Installing and running Scylla Understanding distributed databases Scylla's data model and architecture Working with CQL (Cassandra Query Language) Setting up a Scylla cluster Scylla tools Database administration Troubleshooting Scylla
SQL100 T-SQL Fundamentals with SQL Server Training Course 16 hours This SQL training course is for people who want to acquire basic skills to deal with SQL Server Databases. Course will help the members to learn: How to work with SQL Server and SQL Server Management Studio. Meaning of Databases, SQL and RDBMS etc. How to create tables, use DDL, DML and DAL. Which are the various RDBMS Packages in the market and how they compare with each other. An Introduction to NoSQL and how they are organizations are changing into hybrid databases. Course Outline: What is the meaning of Databases. Comparison of RDBMS and DBMS Different RDBMS available in the market. What is SQL Server? Working with SQL Server Management Studio Working with sublanguages like DDL, DML, DAL. Creation of Tables, data types, Constraints and their definition. Using Insert, Delete and Update statements. Using Select Query and its various operators. Use of Null, Not Null, And, OR, Between, Exists, Order by, Group by, Having clause What are inbuilt functions? Math, String and Datetime functions. Working with Views. How they are used for data access. Working with Joins. Joins types and getting data from multiple tables. Working with Sub Queries. What is a correlated subquery. Difference between Sub Query and Joins. What are Common Table Expressions. Using Recursive Common Table expressions.
sqlsqlsvr SQL in SQL Server 14 hours This SQL training course is for people who want to gain the necessary skills to extract and analyse data from any database and create reports. Course members will learn: how to write SQL queries what relational databases are and how we can use them what are relations and how to create them the structure of data differences between T-SQL and other dialects practical skills for writing queries This SQL course deals with Microsoft T-SQL dialect. If you are interested in generic SQL, please see SQL Fundamentals course. RDBMS (Relational DataBase Management System) Relational Operators SQL as Declarative Language SQL Syntax SQL Sublanguages DQL, DML, DDL, DCL DQL (Data Query Language) in Detail SELECT clause Column aliases Table aliases Date types and Date functions Group function Table joins JOIN clause UNION operator Nested queries Correlated subqueries DML (DataManipulationLanguage) Overview Inserting rows (INSERT) Inserting rows using subquery Updating rows (UPDATE) Deleting rows (DELETE) DDL (Data Definition Language) Overview Creating, altering and dropping objects (CREATE, ALTER, DROP) Creating tables using subquery (CREATE TABLE .... AS SELECT...) CONSTRAINTS Overview NULL i NOT NULL CONSTRAINT clause ENUM type SET type PRIMARY KEY UNIQUE FOREIGN KEY DEFAULT clause Transactions Overview COMMIT ROLLBACK SAVEPOINT Implicit and explicit rollbacks and commits T-SQL Dialects Overview What is Transact-SQL T-SQL and portability with other dialects (what to avoid) Handling Date
3040 Access - Data Base Designing 21 hours The course participants will learn how to design a database and how to adapt it to work with the end user. Database Fundamentals Analysis of the current system Define database items Normalization Relations between the elements Naming standards Create a database Methods for creating arrays (Design View, Wizard, Inputting Data) Data types Field properties Records and operations records Adding and editing a record setting the record Search record Copying tables Create a relational database Keys Relations tables Dependencies Queries Create queries Using the Query Wizard Operations on the results of the query criteria query Calculations and operators in queries Forms and controls Types of controls Using AutoForm Using the wizard forms (Form Wizard) Properties of controls and forms Printing forms. Create a subform (Subform) Headers and footers Reports Create reports. Using AutoReport Using the Report Wizard (Report Wizard) Sections Properties reports Additional tools for forms and reports AutoFormat Special Effects Open a form at runtime database Adding graphics, spell check Switchboards Exporting, importing and linking data Security Passwords Database encryption Security Wizard Backups
3308 Oracle 11g - SQL language for administrators - workshops 21 hours For who The workshop is intended for beginners, starting to work with the Oracle database, future administrators and users of systems based on this database need able to use the SQL language for the extraction and modification of the information contained in the systems. Exams and Certificates The training plan coincides with the material required to pass the exam: 1Z0-051 Oracle Database 11g: SQL Fundamentals I, the first step to getting most certifications Oracle's Database Purpose of training The workshop aims to introduce participants to work with the Oracle database, making them familiar with the SQL language to the extent required for the efficient operation of the system and to take in the future obligations of database applications and Oracle databases. The content of the training The organization of the working environment Introduction to relational databases Extraction of the data using the SELECT statement Modifying data using INSERT, UPDATE, DELETE Overview of schema objects Remarks The workshops are based on 11g XE software Introduction to Oracle Database Architecture Relational model database Users diagrams sessions Tools Introduction to the SELECT statement Screening and selection (WHERE clause) sorting Data types, operators, and service NULL Built-in scalar functions Actions to date National and regional settings in SQL Regular expressions The analysis of aggregated data Grouping functions DISTINCT clause Clauses GROUP BY and HAVING Retrieving data from multiple tables Inner and outer joins (INNER JOIN, OUTER JOIN) ANSI SQL syntax, and other methods connectors (SELF JOIN, NATURAL JOIN) Collective operators (UNION, UNION ALL, INTERSECT, MINUS) Subqueries Subqueries simple Correlated subqueries Operators EXISTS and NOT EXISTS Other types of subqueries Inquiries hierarchical and samples Construction of the tree (CONNECT BY PRIOR clause and START WITH) The SYS_CONNECT_BY_PATH Data samples (SAMPLE clause) Data manipulation (DML) INSERT, UPDATE, DELETE Operations on a large set of (INSERT FIRST INSERT ALL, MERGE) Concurrent users work Transactions Locks FLASHBACK Overview of schema objects Vistas Sequences Synonyms private and public Indexes
mariadbdev MariaDB 10 Developer Course 28 hours Created DBAs, Administrators and developers who are interested with getting involved in MariaDB 10 based on Linux system. Even beginners, who have the basic skill and knowledge on Linux, can catch up with this course just if you follow the instructor's lab and explanation in detail. This course is intended to practice enough Database Concept and SQL and to show it is very easy to understand how to use SQL and manage MariaDB on Linux system. This course will be delivered to audience with 40% lectures, 50% labs and 10% Q&A. This five-day course strongly emphasizes lab-based activities After this course, you can apply the knowledge, which you obtained through this course, to the other database systems such as MySQL, Oracle Database, MSSQL Server and PostgreSQL as well. It can be deliver on any distribution (Ubuntu, CentOS are commonly used) This course covers these kinds of topics: Chapter 00 MariaDB 10 Developer Course Introduction Chapter 01 MariaDB 10 Introduction Chapter 02 Startup MariaDB 10 Chapter 03 MariaDB Tools - Command & GUI Chapter 04 Retrieving Data using SQL Chapter 05 Filtering Data using SQL Chapter 06 Summarizing, Grouping & Combining Chapter 07 Database, Table & Indexes Chapter 08 Inserting, Updating & Deleting Data Chapter 09 Table Joins Chapter 10 Subqueries Chapter 11 Views Chapter 12 Stored Procedures Chapter 13 Triggers Chapter 14 MariaDB Datatypes Chapter 15 Transaction Processing Chapter 16 MariaDB User Management Chapter 17 MariaDB Client Tools
postgresdev PostgreSQL for Developers 14 hours This course provides programmatic interaction with PostgreSQL databases and writing PostgreSQL extensions. Target audience includes developers who want to use or extend PostgreSQL, as well as database architects. What is PostgreSQL? A Brief History of PostgreSQL Conventions Further Information Bug Reporting Guidelines Introduction to PostgreSQL Installation from Packages and Creating Database Installation from Source Code Installation from Source Code on Windows The SQL Language Advanced Features The SQL Language SQL Syntax Data Definition Data Manipulation Queries Data Types Functions and Operators Type Conversion Indexes Full Text Search Concurrency Control Performance Tips Client Interfaces libpq - C Library Large Objects Special Considerations for Event Loop Based Programs Error Handling ECPG - Embedded SQL in C The Information Schema Bindings in Other Programming Languages, e.g. PHP, Perl, Python, Node.js, Go. Special Considerations for Asynchronous Python Frameworks (e.g. gevent, asyncio, Twisted, Tornado) Support of PostgreSQL in ORM frameworks Server Programming Extending SQL Triggers The Rule System Procedural Languages PL/pgSQL - SQL Procedural Language PL/Tcl - Tcl Procedural Language PL/Perl - Perl Procedural Language PL/Python - Python Procedural Language Server Programming Interface Internals Overview of PostgreSQL Internals System Catalogs Frontend/Backend Protocol PostgreSQL Coding Conventions Native Language Support Writing A Procedural Language Handler Writing A Foreign Data Wrapper Genetic Query Optimizer Index Access Method Interface Definition GiST Indexes GIN Indexes Database Physical Storage BKI Backend Interface How the Planner Uses Statistics
kdbplusandq kdb+ and q: Analyze time series data 21 hours kdb+ is an in-memory, column-oriented database and q is its built-in, interpreted vector-based language. In kdb+, tables are columns of vectors and q is used to perform operations on the table data as if it was a list. kdb+ and q are commonly used in high frequency trading and are popular with the major financial institutions, including Goldman Sachs, Morgan Stanley, Merrill Lynch, JP Morgan, etc. In this instructor-led, live training, participants will learn how to create a time series data application using kdb+ and q. By the end of this training, participants will be able to: Understand the difference between a row-oriented database and a column-oriented database Select data, write scripts and create functions to carry out advanced analytics Analyze time series data such as stock and commodity exchange data Use kdb+'s in-memory capabilities to store, analyze, process and retrieve large data sets at high speed Think of functions and data at a higher level than the standard function(arguments) approach common in non-vector languages Explore other time-sensitive applications for kdb+, including energy trading, telecommunications, sensor data, log data, and machine and network usage monitoring Audience Developers Database engineers Data scientists Data analysts Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us.
powerbiforbiandanalytics Power BI for Business Analysts 21 hours Microsoft Power BI is a free Software as a Service (SaaS) suite for analyzing data and sharing insights. Power BI dashboards provide a 360-degree view of the most important metrics in one place, updated in real time, and available on all of their devices. In this instructor-led, live training, participants will learn how to use Microsoft Power Bi to analyze and visualize data using a series of sample data sets. By the end of this training, participants will be able to: Create visually compelling dashboards that provide valuable insights into data Obtain and integrate data from multiple data sources Build and share visualizations with team members Adjust data with Power BI Desktop Audience Business managers Business analystss Data analysts Business Intelligence (BI) and Data Warehouse (DW) teams Report developers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice   Introduction Data Visualization Authoring in Power BI Desktop Creating reports Interacting with reports Uploading reports it to the Power BI Service Revising report layouts Publishing to PowerBI.com Sharing and collaborating with team members Data Modeling Aquiring data Modeling data Security Working with DAX Refreshing the source data Securing data Advanced querying and data modeling Data modeling principals Complex DAX patterns Power BI tips and tricks Closing remarks
pythonmultipurpose Advanced Python 28 hours In this instructor-led training, participants will learn advanced Python programming techniques, including how to apply this versatile language to solve problems in areas such as distributed applications, finance, data analysis and visualization, UI programming and maintenance scripting. Audience Developers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice Notes If you wish to add, remove or customize any section or topic within this course, please contact us to arrange. Introduction Python versatility: from data analysis to web crawling Python data structures and operations Integers and floats Strings and bytes Tuples and lists Dictionaries and ordered dictionaries Sets and frozen sets Data frame (pandas) Conversions Object-oriented programming with Python Inheritance Polymorphism Static classes Static functions Decorators Other Data Analysis with pandas Data cleaning Using vectorized data in pandas Data wrangling Sorting and filtering data Aggregate operations Analyzing time series Data visualization Plotting diagrams with matplotlib Using matplotlib from within pandas Creating quality diagrams Visualizing data in Jupyter notebooks Other visualization libraries in Python Vectorizing Data in Numpy Creating Numpy arrays Common operations on matrices Using ufuncs Views and broadcasting on Numpy arrays Optimizing performance by avoiding loops Optimizing performance with cProfile Processing Big Data with Python Building and supporting distributed applications with Python Data storage: Working with SQL and NoSQL databases Distributed processing with Hadoop and Spark Scaling your applications Python for finance Packages, libraries and APIs for financial processing Zipline PyAlgoTrade Pybacktest quantlib Python APIs Extending Python (and vice versa) with other languages C# Java C++ Perl Others Python multi-threaded programming Modules Synchronizing Prioritizing UI programming with Python Framework options for building GUIs in Python Tkinter Pyqt Python for maintenance scripting Raising and catching exceptions correctly Organizing code into modules and packages Understanding symbol tables and accessing them in code Picking a testing framework and applying TDD in Python Python for the web Packages for web processing Web crawling Parsing HTML and XML Filling web forms automatically Closing remarks
osqlfun ORACLE SQL Fundamentals 21 hours This 3 day course gives an introduction to SQL Developer, SQL*Plus and to SQL, the Structured Query Language used to access a Relational Database and includes the new features of the latest version of ORACLE. The principles learnt may also be applied to databases as diverse as Microsoft SQL Server, MySQL, Access, Informix and DB2. The course takes the format of a workshop, with a mix of lecture, working examples and practical exercises. Although the content may be customised, at least 2 days are needed to cover the core elements. Full course notes are provided along with sample database files, example SQL files and free software tools for use in accessing an ORACLE database. Introduction Overview Aims and Objectives Sample Data Schedule Introductions Pre-requisites Responsibilities Relational Databases The Database The Relational Database Tables Rows and Columns Sample Database Selecting Rows Supplier Table Saleord Table Primary Key Index Secondary Indexes Relationships Analogy Foreign Key Foreign Key Joining Tables Referential Integrity Types of Relationship Many to Many Relationship Resolving a Many-to-Many Relationship One to One Relationship Completing the Design Resolving Relationships Microsoft Access - Relationships Entity Relationship Diagram Data Modelling CASE Tools Sample Diagram The RDBMS Advantages of an RDBMS Structured Query Language DDL - Data Definition Language DML - Data Manipulation Language DCL - Data Control Language Why Use SQL? Course Tables Handout SQL*Plus SQL*Plus Login Easy Connect Using /NOLOG Using SQL*Plus Ending the Session SQL*Plus Commands SQL*Plus Environment SQL*Plus Prompt LOGIN.SQL File Changing the Password Finding Information about Tables Getting Help Where Clause Using SQL Files iSQL*Plus SQL*Plus Commands Data Retrieval SQL Developer SQL Developer - Connection Viewing Table Information Using SQL, Where Clause Using Comments Character Data Users and Schemas AND and OR Clause Using Brackets Date Fields Using Dates Formatting Dates Date Formats TO_DATE TRUNC Date Display Order By Clause DUAL Table Concatenation Selecting Text IN Operator BETWEEN Operator LIKE Operator Common Errors UPPER Function Single Quotes Finding Metacharacters Regular Expressions REGEXP_LIKE Operator Null Values IS NULL Operator NVL Accepting User Input Data Definition Creating a Table Datatypes Simple Create Example Naming Tables Constraints Not Null Primary Key Foreign Key Check Unique Altering Constraints Full Create Example Data Dictionary Alter Table Secondary Indexes B-tree Index Bitmap Index Create Index Explain Plan Using Indexes Clusters Partitioned Tables Creating a Partitioned Table Rename Drop Statement Flashback Table Managing the Recycle Bin Data Update Insert Some Values Insert All Values Insert Date Values Insert TO_DATE Default Values Using Substitution Variables Transactions Commit Rollback Using Constraints Update Date Arithmetic Update TO_DATE TRUNC Delete Truncate Sequences Grant Create Synonym Create Public Synonym Locking Revoke Savepoint Auto Commit Multi-Table Retrieval Calculations Precedence ROUND Function Column Alias Date Arithmetic Using Aliases CEIL and FLOOR Cartesian Product Table Join Table Alias Selecting the Join Column Joining without Selecting Views Dropping Views Finding Views Derived Columns With Check Option Snapshot Views Flashback Query Using Functions TO_CHAR TO_NUMBER LPAD RPAD NVL NVL2 Function DISTINCT Option SUBSTR INSTR Date Functions Aggregate Functions COUNT Group By Clause Rollup and Cube Modifiers Having Clause Grouping By Functions DECODE CASE Workshop Sub-Query & Union Single Row Sub-queries Union Union - All Intersect and Minus Multiple Row Sub-queries Union – Checking Data Outer Join More On Joins Joins Cross Join or Cartesian Product Inner Join Implicit Join Notation Explicit Join Notation Natural Join Equi-Join Cross Join Outer Joins Left Outer Join Right Outer Join Full Outer Join Using UNION Join Algorithms Nested Loop Merge Join Hash Join Reflexive or Self Join Single Table Join Workshop Advanced Queries ROWNUM and ROWID Top N Analysis Inline View Exists and Not Exists Correlated Sub-queries Correlated Sub-queries with Functions Correlated Update Snapshot Recovery Flashback Recovery All Any and Some Operators Insert ALL Merge Sample Data ORDER Tables FILM Tables EMPLOYEE Tables The ORDER Tables The FILM Tables PL/SQL What is PL/SQL? Why Use PL/SQL? Block Structure Sample Code SELECT Statement Using Variables Accepting User Input Exceptions Other DML Statements Creating Procedures Showing Errors Describe a Procedure Calling Procedures Creating and Running Functions Showing Errors Describe a Function Calling Functions Creating Triggers Showing Errors Query Optimisation Query Optimisation Creating The Tables Timing SQL Statements Other Timing Statements Explain Plan Creating the PLAN_TABLE Table Using SET AUTOTRACE Collecting Statistics Primary Key Secondary Indexes The Query Optimizer Rule Based Optimization Cost Based Optimization Choose Keyword Gathering Statistics Optimizer Hints How to Specify Hints Using Indexes Index Types B*tree Indexes Bitmap Indexes Index-organized table When to Create Indexes Choosing Composite Indexes Using Objects Object-oriented Database Object-relational Database Creating Objects Creating Tables with Objects Using Objects in Tables Large Object Support LOB Datatypes Creating Tables with LOBs Inserting an Empty LOB Creating Tables with BFILEs Creating Directories for BFILEs Inserting a BFILE SQL*PLUS REPORTS Objectives ACCEPT and PROMPT Define and Undefine Creating an SQL*Plus Report Break Command Compute Command Saving the Output in a File Utilities What is a Utility? Export Utility Using Parameters Using a Parameter file Import Utility Using Parameters Using a Parameter file Unloading Data Batch Runs SQL*Loader Utility Running the Utility Appending Data
3033 Administering in Microsoft SQL Server 21 hours The course is designed for administrators, developers and database developers. The objectives of the training: acquire and strengthen the skills to create and manage databases knowledge of the syntax and use SQL to retrieve and modify data apply safety rules in the database the use of advanced elements (replication, automation, BI) the use of Microsoft SQL Server capabilities to create complex reports and solutions for developers Basic information about databases Database files, Database Client / Server Relational database management systems (RDBMS) SQL Server versions and the differences between them Express, Standard, Enterprise Workgroup, Mobile , Developer SQL Server Tools SQL Server Management Studio SQL Server Agent Services in SQL Server Database Services Analysis Services Reporting Services Integration Services Base system Master Model Msdb Tempdb Distribution Resource       Create a database The database files and their location File size and its growth Partitioning tables Data Modification Language (DML) INSERT UPDATE DELETE Data Definition Language (DDL) Designing Tables Columns and Attributes Determine the type of data Indexes and Keys Indexes Clustered Indexes Non-Clustered Indexes REBUILD vs. REORGANIZE  Creating a database application Server-side programming Procedures Views Functions Triggers Models play Simple Full Bulk logged Backup Full Differential Transaction Log Backup Strategies Strategy full copy of the database Strategy of full backups and transaction log The strategy of incremental database backup Strategy copy of the database files Basic security and administration of SQL Server Automation Maintenance Plan Jobs Basic security and administration of SQL Server Server Roles Database Roles SA Account Creating Accounts Schemes High Availability Log Shipping Database Mirroring Server Clustering Replication Snapshot Replication Transactional Replication Merge Replication Activity Monitor SQL Server SQL Server Profiler Upgrade In-Place vs. Side-By-Side Service-Pack Cluster Best Practices
3092 SQL language in MSSQL 14 hours The course answers questions How to build a query? What opportunities have SQL? What is a relational database? What is the structure and SQL commands? Relational database models The structure of a relational database Relational operators Download the data Rules for writing SQL queries The syntax for the SELECT Selecting all columns Inquiries from arithmetic operations Aliases columns Literals Concatenation Restrict results The WHERE clause The comparison operators. LIKE Condition Prerequisite BETWEEN ... AND IS NULL condition IN condition. Logical operators Many of the conditions in the WHERE clause The order of operators DISTINCT clause Sorting Data The ORDER BY clause Sorting by multiple columns or expressions SQL Functions The differences between the functions of single and multi-rows Functions text, numeric, date, Conversion functions Nesting functions Handling of NULL values Aggregating data using the grouping function Grouping functions How grouping functions treat NULL values Create groups of data - the GROUP BY clause Grouping multiple columns Reducing the function result grouping - the HAVING clause Retrieving data from multiple tables Types of joins Aliases tables Joins in the WHERE clause INNER JOIN Inner join External Merge LEFT, RIGHT Cartesian product Subqueries Place subqueries in the SELECT command Subqueries single and multi-lineage Operators Subqueries single-line Operators Subqueries multi-IN, ALL, ANY Collective operators UNION operator INTERSECT operator EXCEPT operator Insert, update, and delete data INSERT command UPDATE command DELETE command Transactions
mean1 Building Web Apps using the MEAN stack 35 hours Course Objective: MEAN stack is a full-stack JavaScript solution that helps you write scalable, robust, and maintainable web applications quickly and easily using MongoDB, express, AngularJS, and Node.js. By the end of this hands-on intensive training course, the students will be able to: Store the data in NoSQL, document-oriented MongoDB database that brings performance and scalability. Use Node.js, the server-side platform built on Google V8’s runtime for building fast, scalable network applications. Use Express, a simple yet powerful web application development HTTP server framework built on top of Node.js. Use AngularJS framework that offers declarative, two-way data binding for web applications. Take advantage of the ‘full-stack JavaScript’ paradigm i.e. store documents in JSON-like format in MongoDB, author JSON queries in Node.js/Express.js, and forward these JSON documents back to an Angular-based frontend. Get acquainted with the latest web application development trends in the IT industry. Node.js Getting started with Node.js Node Package Manager Modules Asynchronous Programming Callbacks Events Streams Web Sockets Angular.js Angular Architecture Modules, Controllers and Scope Views Two-way Binding Built-in and Custom Directives Event Directives Expressions Built-in and Custom Filters Understanding the Digest Loop Forms and Validation AngularJS Service Types Factories, Providers, Decorators, DI Creating Custom Services Consuming Ajax Web Services via $http and $resource Routing, Redirects, and Promises Express.js MVC Pattern Introduction to Express Routing HTTP Interaction Handling Form Data Handling Query Parameters Cookies and Sessions User Authentication Error Handling Creating and Consuming RESTful Services Using Templates MongoDB Understanding NoSQL MongoDB Finding Documents Update, Insert, and Upsert Indexing Data Modeling Aggregation
Imp Impala for Business Intelligence 21 hours Cloudera Impala is an open source massively parallel processing (MPP) SQL query engine for Apache Hadoop clusters. Impala enables users to issue low-latency SQL queries to data stored in Hadoop Distributed File System and Apache Hbase without requiring data movement or transformation. Audience This course is aimed at analysts and data scientists performing analysis on data stored in Hadoop via Business Intelligence or SQL tools. After this course delegates will be able to Extract meaningful information from Hadoop clusters with Impala. Write specific programs to facilitate Business Intelligence in Impala SQL Dialect. Troubleshoot Impala. Introduction to Impala What is Impala? How Impala Differs from Relational Databases Limitations and Future Directions Using the Impala Shell The Impala Daemon, Statestore and Catalogue service Loading Impala Explore a New Impala Instance Load CSV Data from Local Files Point an Impala Table at Existing Data Files Analyzing Data with Impala Describe the Impala Table Basic Syntax and Querying Data Types Filtering, Sorting, and Limiting Results Joining and Grouping Data Data Loading and Querying Examples Improving Impala Performance How Impala works with Hadoop file formats Hands-On Exercise: Interactive Analysis with Impala Programming Impala Applications Overview of the Impala SQL Dialect Overview of Impala Programming Interfaces Troubleshooting Impala Troubleshooting Impala SQL Syntax Issues Troubleshooting I/O Capacity Problems Impala Web User Interface for Debugging    
riak Riak: Build Applications with High Data Accuracy 14 hours Riak is an Erlang based open-source document database, similar to CouchDB. It is created and maintained by Basho. In this instructor-led, live training, participants will learn how to build, run and operate a Riak based web application. By the end of this training, participants will be able to: Extend the number of hardware nodes and partition data across multiple servers Use bucket/key/values to organize and retrieve documents Use full-text search like query syntax Understand other Riak related technologies, such as Riak KV and Riak TS Test, secure, optimize and deploy a sample web application Audience Developers Database engineers Operations staff Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us.
druid Druid: Build a fast, real-time data analysis system 21 hours Druid is an open-source, column-oriented, distributed data store written in Java. It was designed to quickly ingest massive quantities of event data and execute low-latency OLAP queries on that data. Druid is commonly used in business intelligence applications to analyze high volumes of real-time and historical data. It is also well suited for powering fast, interactive, analytic dashboards for end-users. Druid is used by companies such as Alibaba, Airbnb, Cisco, eBay, Netflix, Paypal, and Yahoo. In this course we explore some of the limitations of data warehouse solutions and discuss how Druid can compliment those technologies to form a flexible and scalable streaming analytics stack. We walk through many examples, offering participants the chance to implement and test Druid-based solutions in a lab environment. Audience     Application developers     Software engineers     Technical consultants     DevOps professionals     Architecture engineers Format of the course     Part lecture, part discussion, heavy hands-on practice, occasional tests to gauge understanding Introduction Installing and starting Druid Druid architecture and design Real-time ingestion of event data Sharding and indexing Loading data Querying data Visualizing data Running a distributed cluster Druid + Apache Hive Druid + Apache Kafka Druid + others Troubleshooting Administrative tasks
neo4j Beyond the relational database: neo4j 21 hours Relational, table-based databases such as Oracle and MySQL have long been the standard for organizing and storing data. However, the growing size and fluidity of data have made it difficult for these traditional systems to efficiently execute highly complex queries on the data. Imagine replacing rows-and-columns-based data storage with object-based data storage, whereby entities (e.g., a person) could be stored as data nodes, then easily queried on the basis of their vast, multi-linear relationship with other nodes. And imagine querying these connections and their associated objects and properties using a compact syntax, up to 20 times lighter than SQL. This is what graph databases, such as neo4j offer. In this hands-on course, we will set up a live project and put into practice the skills to model, manage and access your data. We contrast and compare graph databases with SQL-based databases as well as other NoSQL databases and clarify when and where it makes sense to implement each within your infrastructure. Audience Database administrators (DBAs) Data analysts Developers System Administrators DevOps engineers Business Analysts CTOs CIOs Format of the course Heavy emphasis on hands-on practice. Most of the concepts are learned through samples, exercises and hands-on development. Getting started with neo4j neo4j vs relational databases neo4j vs other NoSQL databases Using neo4j to solve real world problems Installing neo4j Data modeling with neo4j Mapping white-board diagrams and mind maps to neo4j Working with nodes Creating, changing and deleting nodes Defining node properties Node relationships Creating and deleting relationships Bi-directional relationships Querying your data with Cypher Querying your data based on relationships MATCH, RETURN, WHERE, REMOVE, MERGE, etc. Setting indexes and constraints Working with the REST API REST operations on nodes REST operations on relationships REST operations on indexes and constraints Accessing the core API for application development Working with NET, Java, Javascript, and Python APIs Closing remarks  
oplsqlfun ORACLE PL/SQL Fundamentals 21 hours This 3 day course gives an introduction to ORACLE PL/SQL, an application development environment that enables the writing of stored procedures, functions and triggers using both SQL and PL/SQL commands. The course takes the format of a workshop, with a mix of lecture, working examples and practical exercises. Although the content may be customised, at least 2 days are needed to cover the core elements. Full course notes are provided along with sample database files, example SQL files and free software tools for use in accessing an ORACLE database. Introduction Aims and Objectives Course Schedule Introductions Pre-requisites Responsibilities SQL Tools Objectives SQL Developer SQL Developer - Connection Viewing Table Information Using SQL, SQL Developer - Query SQL*Plus Login Direct Connection Using SQL*Plus Ending the Session SQL*Plus Commands SQL*Plus Environment SQL*Plus Prompt Finding Information about Tables Getting Help Using SQL Files iSQL*Plus, Entity Models The ORDERS Tables The FILM Tables Course Tables Handout SQL Statement Syntax SQL*Plus Commands What is PL/SQL? What is PL/SQL? Why Use PL/SQL? Block Structure Displaying a Message Sample Code Setting SERVEROUTPUT Update Example, Style Guide Variables Variables Datatypes Setting Variables Constants Local and Global Variables %Type Variables Substitution Variables Comments with & Verify Option && Variables Define and Undefine SELECT Statement SELECT Statement Populating Variables %Rowtype Variables CHR Function Self Study PL/SQL Records Example Declarations Conditional Statement IF Statement SELECT Statement Self Study Case Statement Trapping Errors Exception Internal Errors Error Code and Message Using No Data Found User Exceptions Raise Application Error Trapping Non-defined Errors Using PRAGMA EXCEPTION_INIT Commit and Rollback Self Study Nested Blocks Workshop Iteration - Looping Loop Statement While Statement For Statement Goto Statement and Labels Cursors Cursors Cursor Attributes Explicit Cursors Explicit Cursor Example Declaring the Cursor Declaring the Variable Open, Fetching the First Row Fetching the Next Row Exit When %Notfound Close For Loop I For Loop II Update Example FOR UPDATE FOR UPDATE OF WHERE CURRENT OF Commit with Cursors Validation Example I Validation Example II Cursor Parameters, Workshop Workshop Solution Procedures, Functions and Packages Create Statement Parameters Procedure Body Showing Errors Describe a Procedure Calling Procedures Calling Procedures in SQL*Plus Using Output Parameters Calling with Output Parameters Creating Functions Example Function Showing Errors Describe a Function Calling Functions Calling Functions in SQL*Plus Modular Programming Example Procedure Calling Functions Calling Functions In An IF Statement Creating Packages Package Example Reasons for Packages Public and Private Sub-programs Showing Errors Describe a Package Calling Packages in SQL*Plus Calling Packages From Sub-Programs Dropping a Sub-Program Finding Sub-programs Creating a Debug Package Calling the Debug Package Positional and Named Notation Parameter Default Values Recompiling Procedures and Functions Workshop Triggers Creating Triggers Statement Triggers Row Level Triggers WHEN Restriction Selective Triggers - IF Showing Errors Commit in Triggers Restrictions Mutating Triggers Finding Triggers Dropping a Trigger Generating an Auto-number Disabling Triggers Enabling Triggers Trigger Names Sample Data ORDER Tables FILM Tables EMPLOYEE Tables Dynamic SQL SQL in PL/SQL Binding Dynamic SQL Native Dynamic SQL DDL and DML DBMS_SQL Package Dynamic SQL - SELECT Dynamic SQL - SELECT Procedure Using Files Using Text Files UTL_FILE Package Write/Append Example Read Example Trigger Example DBMS_ALERT Packages DBMS_JOB Package COLLECTIONS %Type Variables Record Variables Collection Types Index-By Tables Setting Values Nonexistent Elements Nested Tables Nested Table Initialisation Using the Constructor Adding to a Nested Table Varrays Varray Initialization Adding Elements to a Varray Multilevel Collections Bulk Bind Bulk Bind Example Transactional Issues BULK COLLECT Clause RETURNING INTO Ref Cursors Cursor Variables Defining REF CURSOR Types Declaring Cursor Variables Constrained and Unconstrained Using Cursor Variables Cursor Variable Examples
3044 Using and managing the database in MySQL 14 hours Participant will learn: Can I use MySQL for free? What do I offer a commercial license? How to install a MySQL database? How to perform basic operations on the installation? What are the available tools for managing and programming in a MySQL database? Legal aspect MySQL MySQL's dual license policies Commercial License Open Source License Installing MySQL Standard installation of MySQL (binary files) Installing MySQL on Windows or Unix-like (GNU / Linux, FreeBSD) Tuning the server after installation, testing Upgrading MySQL Connecting to the server Making queries Creating and using databases Creating and selecting a database Creating tables Importing data into the table Obtaining information about the database and tables Using the mysql command in batch (Batch Mode) Discussion of the utilities Ways to call the program Setting program options (command line, the configuration file, environment variables) Setting the program variables via command line GUI tools for managing and programming the database MySQL Administrator MySQL Query Browser Toad for MySQL
3082 Microsoft Access - download the data 14 hours The course is designed for persons with pre-information databases using SQL queries or queries. Queries The types of queries Query Wizard Query Design View query Properties Grouping in Queries Create a simple select query Crosstab queries Query the search duplicates Not matching the search query data Parameter queries Queries (forming a table, delete, append, updating) Create a table with a query Archiving data using an append query Troubleshoot queries Expressions in Queries Examples of the use of expressions Calculations in queries Functions SQL in Access Download the data Restrict results Sorting Data SQL Functions Aggregating data using the grouping Retrieving data from multiple tables subqueries Operators collective
trafodionadm1 Administering Trafodion 14 hours NewSQL Concepts  Installation 4 Migrating or Loading Data Connecting to the Database Trafodion SQL vs ANSI SQL Command Interface Managing Cluster
seqdb SequoiaDB for Developers 14 hours SequoiaDB is a document-oriented NewSQL database that supports JSON transaction processing and SQL query. SequoiaDB can directly interface with applications to provide high performance and horizontally scalable data storage and processing functions, or serve as the frontend to Hadoop and Spark for both real-time query and data analysis. Audience This course assumes prior knowledge of SQL and is targeted at engineers seeking to deploy and integrate SequoiaDB instances. After completing this course, delegates will: understand SequoiaDB’s structure and deployment mechanisms be able to carry out installation / production environment / architecture tasks and configuration be able to assess code quality, perform debugging, monitoring be able to implement advanced production like integration, migration and development Using SequoiaDB Starting SequoiaDB Connectors (Hadoop/Hive/Map Reduce) Basic Operators with reference Developing for SequoiaDB Data Models SequoiaDB Shell SQL to SequiaDB mapping Aggregation Reference Operator SequoiaDB Shell SQL to SequoiaDB mapping list Error List
hypertable Hypertable: Deploy a BigTable like database 14 hours Hypertable was an open-source software database management system based on the design of Google's Bigtable. In this instructor-led, live training, participants will learn how to set up and manage a Hypertable database system. By the end of this training, participants will be able to: Install, configure and upgrade a Hypertable instance Set up and administer a Hypertable cluster Monitor and optimize the performance of the database Design a Hypertable schema Work with Hypertable's API Troubleshoot operational issues Audience Developers Operations engineers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us.
matlabpredanalytics Matlab for Predictive Analytics 21 hours Predictive analytics is the process of using data analytics to make predictions about the future. This process uses data along with data mining, statistics, and machine learning techniques to create a predictive model for forecasting future events. In this instructor-led, live training, participants will learn how to use Matlab to build predictive models and apply them to large sample data sets to predict future events based on the data. By the end of this training, participants will be able to: Create predictive models to analyze patterns in historical and transactional data Use predictive modeling to identify risks and opportunities Build mathematical models that capture important trends Use data to from devices and business systems to reduce waste, save time, or cut costs Audience Developers Engineers Domain experts Format of the course Part lecture, part discussion, exercises and heavy hands-on practice Introduction     Predictive analytics in finance, healthcare, pharmaceuticals, automotive, aerospace, and manufacturing Overview of Big Data concepts Capturing data from disparate sources What are data-driven predictive models? Overview of statistical and machine learning techniques Case study: predictive maintenance and resource planning Applying algorithms to large data sets with Hadoop and Spark Predictive Analytics Workflow Accessing and exploring data Preprocessing the data Developing a predictive model Training, testing and validating a data set Applying different machine learning approaches ( time-series regression, linear regression, etc.) Integrating the model into existing web applications, mobile devices, embedded systems, etc. Matlab and Simulink integration with embedded systems and enterprise IT workflows Creating portable C and C++ code from MATLAB code Deploying predictive applications to large-scale production systems, clusters, and clouds Acting on the results of your analysis Next steps: Automatically responding to findings using Prescriptive Analytics Closing remarks
flockdb Flockdb: A simple graph database for social media 7 hours FlockDB is an open source distributed, fault-tolerant graph database for managing wide but shallow network graphs. It was initially used by Twitter to store relationships among users In this instructor-led, live training, participants will learn how to setup and use a FlockDB database to help answer social media questions such as who follows whom, who blocks whom, etc. By the end of this training, participants will be able to: Install and configure FlockDB Understand the unique features of FlockDB, relative to other graph databases such Neo4j Use FlockDB to maintain a large graph dataset Use FlockDB together with MySQL to provide provide distributed storage capabilities Query, create and update extremely fast graph edges Scale FlockDB horizontally for use in on-line, low-latency, high throughput web environments Audience Developers Database engineers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us.
advsqlpt Advanced SQL, Stored Procedures and Triggers for Microsoft SQL Server 14 hours The aim of this course is to provide a clear understanding of the advanced use of (SQL) for Microsoft SQL Server and the advanced use of Transact-SQL. For more in depth coverage of the topics this course can be run as a three day course. Review of Structured Query Language DQL, DML, DDL The GROUP BY, HAVING Clause Sub-queries and Correlated Sub-queries Advanced Update & Delete Statements Sub-queries Correlated Sub-queries Procedural Programming Variables Control-Of-Flow Statements IF, WHILE, CASE, GOTO, RETURN Managing Errors Responding To Errors RAISERROR PRINT Using Transactions Introduction To Transactions Transaction Isolation Levels Deadlocks Transactional Error Handling Implementing Cursors Declaring Cursors OPEN, FETCH, CLOSE DEALLOCATE CURRENT OF Stored Procedures Creating Stored Procedures Passing values into a Stored Procedure Returning Information From Stored Procedures Altering Stored Procedures Triggers Creating Triggers Transactional Error Handling Using Inserted and Deleted Tables
1126 Database Version Control (dbv) 7 hours This course show a solution for sharing and versioning your db schema. It contains exercises which cover: common scenarios in a software development with sharing database changes using the dbv to debug problems related to database schema changes dbv.php Installing Optional Settings Pushing schema objects Receiving schema objects Creating revisions Receiving revisions
838 Oracle Database 10g: Administration Workshop I Release 2 35 hours What you will learn This course is designed to give you a firm foundation in basic database administration. Expert instructors will teach you how to install and maintain an Oracle database. Learn To: Install the Database. Back up and recover data. Administer users and manage data. Transport data between databases. Configure the network. Understand the Oracle database architecture and how its components work and interact with one another. Use performance monitoring, database security, user management and backup/recovery techniques. Create an Operational Database This course will also teach you how to create an operational database and properly manage the various structures efficiently. The lesson topics are reinforced with structured, hands-on practices that solidify your understanding. Prepare for Oracle Certification Exams This course is designed to prepare you for the corresponding Oracle Certified Associate exam. It counts towards the hands-on course requirement for the Oracle Database 10g Administrator Certification Audience Database Administrators Database Designers Project Manager Sales Consultants Support Engineer Technical Consultant Course Objectives Install Oracle Database 10g and configure a database Manage the Oracle instance Manage the Database storage structures Create and administer user accounts Perform backup and recovery of a database Monitor, troubleshoot, and maintain a database Configure Oracle Net services Move data between databases and files Introduction (Database Architecture) Describe course objectives Explore the Oracle 10g database architecture Installing the Oracle Database Software Explain core DBA tasks and tools Plan an Oracle installation Use optimal flexible architecture Install software with the Oracle Universal Installer (OUI) Creating an Oracle Database Create a database with the Database Configuration Assistant (DBCA) Create a database design template with the DBCA Generate database creation scripts with the DBCA Managing the Oracle Instance Start and stop the Oracle database and components Use Enterprise Manager (EM) Access a database with SQL*Plus and iSQL*Plus Modify database initialization parameters Understand the stages of database startup View the Alert log Use the Data Dictionary Managing Database Storage Structures Describe table data storage (in blocks) Define the purpose of tablespaces and data files Understand and utilize Oracle Managed Files (OMF) Create and manage tablespaces Obtain tablespace information Describe the main concepts and functionality of Automatic Storage Management (ASM) Administering User Security Create and manage database user accounts Authenticate users Assign default storage areas (tablespaces) Grant and revoke privileges Create and manage roles Create and manage profiles Implement standard password security features Control resource usage by users Managing Schema Objects Define schema objects and data types Create and modify tables Define constraints View the columns and contents of a table Create indexes, views and sequences Explain the use of temporary tables Use the Data Dictionary Managing Data and Concurrency Manage data through SQL Identify and administer PL/SQL Objects Describe triggers and triggering events Monitor and resolve locking conflicts Managing Undo Data Explain DML and undo data generation Monitor and administer undo Describe the difference between undo and redo data Configure undo retention Guarantee undo retention Use the undo advisor Implementing Oracle Database Security Describe DBA responsibilities for security Apply the principal of least privilege Enable standard database auditing Specify audit options Review audit information Maintain the audit trail Configuring the Oracle Network Environment Use Enterprise Manager for configuring the Oracle network environment Create additional listeners Create Net Service aliases Configure connect-time failover Control the Oracle Net Listener Test Oracle Net connectivity Identify when to use shared versus dedicated servers Proactive Maintenance Use statistics Manage the Automatic Workload Repository (AWR) Use the Automatic Database Diagnostic Monitor (ADDM) Describe advisory framework Set alert thresholds Use server-generated alerts Use automated tasks Performance Management Use Enterprise Manager pages to monitor performance Use the SQL Tuning Advisor Use the SQL Access Advisor Use Automatic Shared Memory Management Use the Memory Advisor to size memory buffers Use performance related dynamic views Troubleshoot invalid or unusable objects Backup and Recovery Concepts Identify the types of failure that may occur in an Oracle Database Describe ways to tune instance recovery Identify the importance of checkpoints, redo log files, and archived log files Configure ARCHIVELOG mode Performing Database Backups Create consistent database backups Back your database up without shutting it down Create incremental backups Automate database backups Monitor the flash recovery area Performing Database Recovery Recover from loss of a control file Recover from loss of a redo log file Perform complete recovery following the loss of a data file Performing Flashback Describe Flashback database Restore the table content to a specific point in the past with Flashback Table Recover from a dropped table View the contents of the database as of any single point in time with Flashback Query See versions of a row over time with Flashback Versions Query View the transaction history of a row with Flashback Transaction Query Moving Data Describe available ways for moving data Create and use directory objects Use SQL*Loader to load data from a non-Oracle database (or user files) Explain the general architecture of Data Pump Use Data Pump Export and Import to move data between Oracle databases Use external tables to move data via platform-independent files
68962 MySQL Administration 32 hours Audience: Any IT professionals who aspire to become DBAs or database support professionals on MySql Database on linx/windows platforms. Format: 40% theoretical/lectures, 60%Practical/hands on lab Introduction MySQL Overview, Products, Services MySQL Services and Support Supported Operating Services Training Curriculum Paths MySQL Documentation Resources MySQL Architecture The client/server model Communication protocols The SQL Layer The Storage Layer How the server supports storage engines How MySQL uses memory and disk space The MySQL plug-in interface System Administration Choosing between types of MySQL distributions Installing the MySQL Server The MySQL Server installation file structure Starting and stopping the MySQL server Upgrading MySQL Running multiple MySQL servers on a single host Server Configuration MySQL server configuration options System variables SQL Modes Available log files Binary logging Clients and Tools Available clients for administrative tasks MySQL administrative clients The mysql command-line client The mysqladmin command-line client The MySQL Workbench graphical client MySQL tools Available APIs (drivers and connectors) Data Types Major categories of data types Meaning of NULL Column attributes Character set usage with data types Choosing an appropriate data type Obtaining Metadata Available metadata access methods Structure of INFORMATION_SCHEMA Using the available commands to view metadata Differences between SHOW statements and INFORMATION_SCHEMA tables The mysqlshow client program Using INFORMATION_SCHEMA queries to create shell commands and SQL statements Transactions and Locking Using transaction control statement to run multiple SQL statements concurrently The ACID properties of transactions Transaction isolation levels Using locking to protect transactions Storage Engines Storage engines in MySQL InnoDB storage engine InnoDB system and file-per-table tablespaces NoSQL and the Memcached API Configuring tablespaces efficiently Using foreign keys to attain referential integrity InnoDB locking Features of available storage engines Partitioning Partitioning and its use in MySQL Reasons for using partitioning Types of partitioning Creating partitioned tables Subpartitioning Obtaining partition metadata Modifying partitions to improve performance Storage Engine Support of Partitioning User Management Requirements for user authentication Using SHOW PROCESSLIST to show which threads are running Creating, modifying and dropping user accounts Alternative authentication plugins Requirements for user authorization Levels of access privileges for users Types of privileges Granting, modifying and revoking user privileges Security Recognizing common security risks Security risks specific to the MySQL installation Security problems and counter-measures for network, operating system, filesystem and users Protecting your data Using SSL for secure MySQL server connections How SSH enables a secure remote connection to the MySQL server Finding additional information for common security issues Table Maintenance Types of table maintenance operations SQL statements for table maintenance Client and utility programs for table maintenance Maintaining tables for other storage engines Exporting and Importing Data Exporting Data Importing Data Programming Inside MySQL Creating and executing Stored Routines Describing stored routine execution security Creating and executing triggers Creating, altering and dropping events Event execution scheduling MySQL Backup and Recovery Backup basics Types of backup Backup tools and utilities Making binary and text backups Role of log and status files in backups Data Recovery Replication Managing the MySQL Binary Log MySQL replication threads and files Setting up a MySQL Replication Environment Designing Complex Replication Topologies Multi-Master and Circular Replication Performing a Controlled Switchover Monitoring and Troubleshooting MySQL Replication Replication with Global Transaction Identifiers (GTIDs) Introduction to Performance Tuning Using EXPLAIN to Analyze Queries General Table Optimizations Monitoring status variables that affect performance Setting and Interpreting MySQL server Variables Overview of Performance Schema Conclusion Q&A Session
couch Apache CouchDB for Developers 14 hours Adobe CouchDB is a scalable, fault-tolerant, and schema-free document-oriented database written in Erlang. It's used in large and small organizations for a variety of applications where a traditional SQL database isn't the best solution for the problem at hand. Audience This course is directed at engineers and developers seeking to deploy and develop with a CouchDB instance. Installing CouchDB Introduction: CouchDB at a glance  Installation: Get up and running fast  Technical Overview: Details of the CouchDB technology  Basics: Getting started with CouchDB  Configuring CouchDB Base Configuration couch_peruser CouchDB HTTP Server Authentication and Authorization Compaction Configuration Logging Replicator Query Servers External Processes HTTP Resource Handlers CouchDB Internal Services Miscellaneous Parameters Proxying Configuration CouchApp CouchDB External APIs Query Server Fauxton  Cluster Setup Theory Node Management Database Management Sharding JSON Structure All Database Documents Bulk Documents Troubleshooting Breaking Changes Error Messages Known Problem Official CouchDB bug tracker
globalsight Globalsight: Automate the localization process 7 hours Globalight is an open-source, Java based application server for automating, streamlining, and managing the localization process. In this instructor-led, live training, participants will learn about Globalsight's architecture and functionality as they install, configure and deploy a demonstration server . By the end of this training, participants will be able to: Undertand the benefits of Globalsight relative to other Translation Management Systems Install Globalsight server and related components Set up Globalsight to work behind a reverse proxy Build and deploy Globalsight to a production environment Troubleshoot and optimize Globalsight Use Globalsight's APIs to integrate it with third party applications, including JBPM, etc. Audience System administrators Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us.
voldemort Voldemort: Setting up a key-value distributed data store 14 hours Voldemort is an open-source distributed data store that is designed as a key-value store.  It is used at LinkedIn by numerous critical services powering a large portion of the site. This course will introduce the architecture and capabilities of Voldomort and walk participants through the setup and application of a key-value distributed data store. Audience     Software developers     System administrators     DevOps engineers Format of the course     Part lecture, part discussion, heavy hands-on practice, occasional tests to gauge understanding Introduction Understanding distributed key-value storage systems Voldomort data model and architecture Downloading and configuration Command line operations Clients and servers Working with Hadoop Configuring build and push jobs Rebalancing a Voldemort instance Serving Large-scale Batch Computed Data Using the Admin Tool Performance tuning
meanangular4 Angular 4: Building Web Apps using the MEAN stack 35 hours Angular 4 (previous versions referred to as: Angular.js, AngularJS, AngularJS 1, Angular 1, Angular 2, etc.) is a JavaScript-based front-end web application framework for developing single-page applications. It boasts better performance over its predecessor, more APIs to tap into, and improved design and responsiveness on mobile devices. MEAN stack is a full-stack JavaScript solution for writing scalable, robust, and maintainable web applications quickly and easily using MongoDB, Express, Angular, and Node.js. In this instructor-led, live training, participants will learn how to use the MEAN stack, specifically using Angular 4, as they step through the creation and deployment of a sample web application. By the end of this training, participants will be able to: Create, build, debug and deploy a MEAN-based Angular 4 application Unit test their Angular 4 application Write Angular code using TypeScript Audience Developers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us.  
416 Introduction to Firebird 14 hours Classic, SuperClassic or Superserver? Installation packages Embedded Server for Windows What is in the kit? Default disk locations Linux Windows Installing Firebird Installing the Firebird server Installing multiple servers Testing your installation Performing a client-only install Server configuration and management User management: gsec Security Windows Control Panel applets Administration tools Working with databases Connection strings Connecting to an existing database Creating a database using isql Firebird SQL Protecting your data Backup How to corrupt a database
3165 Visual Basic for Applications (VBA) and Databases 14 hours The training is designed for people using Excel and VBA for access to the databases. The use of external data sources Using ADO library Access to the database via ODBC References to external data sources Objects ADO: Connection Command Recordset Chain connection - connection string Create connections to different databases: Microsoft Access, Oracle, MySQL Advanced Access Database ADOX library and the ability to modify the database structure Calling parameterized queries Exporting a set of records to XML Importing XML file VBA Form Custom forms, access to databases Use the forms in the sheet Forms to run queries on the database share
564 Java SE 7 Programmer Certification Preparation 21 hours Java Basics Working With Java Data Types Using Operators and Decision Constructs Creating and Using Arrays Using Loop Constructs Working with Methods and Encapsulation Working with Inheritance Handling Exceptions Java Class Design Advanced Class Design Object-Oriented Design Principles Generics and Collections String Processing Exceptions and Assertions Java I/O Fundamentals Java File I/O (NIO.2) Building Database Applications with JDBC Threads Concurrency Localization
osqlide Oracle SQL Intermediate - Data Extraction 14 hours Limiting results The WHERE clause Comparison operators LIKE Condition Prerequisite BETWEEN ... AND IS NULL condition Condition IN Boolean operators AND, OR and NOT Many of the conditions in the WHERE clause The order of the operators. DISTINCT clause SQL functions The differences between the functions of one and multilines Features text, numeric, date, Explicit and implicit conversion Conversion functions Nesting functions Viewing the performance of the functions - dual table Getting the current date function SYSDATE Handling of NULL values Aggregating data using the grouping function Grouping functions How grouping functions treat NULL values Create groups of data - the GROUP BY clause Grouping multiple columns Limiting the function result grouping - the HAVING clause Subqueries Place subqueries in the SELECT command Subqueries single and multi-lineage Operators Subqueries single-line Features grouping in subquery Operators Subqueries multi-IN, ALL, ANY How NULL values ​​are treated in subqueries Operators collective UNION operator UNION ALL operator INTERSECT operator MINUS operator Further Usage Of Joins Revisit Joins Combining Inner and Outer Joins Partitioned Outer Joins Hierarchical Queries Further Usage Of Sub-Queries Revisit sub-queries Use of sub-queries as virtual tables/inline views and columns Use of the WITH construction Combining sub-queries and joins Analytics functions OVER clause Partition Clause Windowing Clause Rank, Lead, Lag, First, Last functions Retrieving data from multiple tables (if time at end) Types of connectors The use NATURAL JOIN Aliases tables Joins in the WHERE clause INNER JOIN Inner join External Merge LEFT, RIGHT, FULL OUTER JOIN Cartesian product Aggregate Functions (if time at end) Revisit Group By function and Having clause Group and Rollup Group and Cube
kylin Apache Kylin: From classic OLAP to real-time data warehouse 14 hours Apache Kylin is an extreme, distributed analytics engine for big data. In this instructor-led live training, participants will learn how to use Apache Kylin to set up a real-time data warehouse. By the end of this training, participants will be able to: Consume real-time streaming data using Kylin Utilize Apache Kylin's powerful features, including snowflake schema support, a rich SQL interface, spark cubing and subsecond query latency Note We use the latest version of Kylin (as of this writing, Apache Kylin v2.0) Audience Big data engineers Big Data analysts Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us.
couchad Apache CouchDB for Administrators 21 hours Adobe CouchDB is a scalable, fault-tolerant, and schema-free document-oriented database written in Erlang. It's used in large and small organizations for a variety of applications where a traditional SQL database isn't the best solution for the problem at hand. Audience This course is directed at administrators and developers seeking to maintain a CouchDB instance. Installing CouchDB Introduction: CouchDB at a glance  Technical Overview: Details of the CouchDB technology  Basics: Getting started with CouchDB  Configuring CouchDB Base Configuration couch_peruser CouchDB HTTP Server Authentication and Authorization Compaction Configuration Logging Replicator Query Servers External Processes HTTP Resource Handlers CouchDB Internal Services Miscellaneous Parameters Proxying Configuration Replication Triggering Replication Replication Procedure Master - Master replication Controlling which Documents to Replicate Migrating Data to Clients Maintainence Compaction Database Compaction Views Compaction Views cleanup Automatic Compaction Performance Disk I/O File Size Disk and File System Performance System Resource Limits CouchDB Configuration Options delayed_commits max_dbs_open Erlang PAM and ulimit Network CouchDB DELETE operation Document’s ID Views Views Generation Builtin Reduce Functions Troubleshooting Breaking Changes Error Messages Known Problem Official CouchDB bug tracker
meteor Meteor: Use JavaScript to develop cross-platform mobile applications 14 hours Meteor (aka MeteorJS) is an open-source JavaScript web framework written in Node.js. It integrates with MongoDB and enables rapid prototyping of Android and iOS applications. This course introduces the fundamentals of Meteor and walks participants through the creation of a real-time web applications for both desktop and mobile platforms. Audience     Front-end developers     Anyone interested in learning Meteor Format of the course     Overview of Meteor's features and capabilities along with step-by-step development of a mobile application for iOS and Android. Introduction to Meteor JavaScript Installing Meteor Meteor architecture Overview of MongoDB Creating a Meteor application Meteor's project file structure Creating a Template and Collections Working with Forms and Events Sessions and Trackers in Meteor Working with the the Core API Working with HTTP, Email, Assets Creating a database in Meteor Building database collections Sorting the data in Meteor Building a user accounts system Creating packages in Meteor Deploying your application
dnswebmaildb Top 4 Linux/Unix Servers - DNS,Web,Mail and Database 28 hours Created Linux/Unix Administrators and developers who are interested with getting involved in LInux/Unix Servers Even beginners, who have the basic skill and knowledge on Linux, can catch up with this course just if you follow the instructor's lab and explanation in detail. This course is intended to practice enough Managing Linux Servers and to show it is very easy to understand Linux/Unix servers. This course will be delivered to audience with 40% lectures, 50% labs and 10% Q&A. This five-day course strongly emphasizes lab-based activities. You'll learn how to deploy and manage Top 4 Linux Servers that provide highly useful network services to a mission-critical enterprise environment. It can be deliver on any distribution (Fedora, CentOS are commonly used) This course covers these kinds of topics: Bind as a ;DNS server Apache as a Web Server Postfix as a Mail Server MariaDB as a Database Server Through this course, you will learn from the installation to High level features of each server.
pgsqladm PostgreSQL Administration and Development 28 hours This course handles the administration and performance tuning of PostgreSQL databases. Attendees will learn the use of specialised PostgreSQL (AKA Postgres) modules such as replication, connection pooling and full text searching. What is PostgreSQL? A Brief History of PostgreSQL Conventions Further Information Bug Reporting Guidelines Introduction to PostgreSQL Installation and Creating Database The SQL Language Advanced Features The SQL Language SQL Syntax Data Definition Data Manipulation Queries Data Types Functions and Operators Type Conversion Indexes Full Text Search Concurrency Control Performance Tips Server Administration Installation from Source Code Installation from Source Code on Windows Server Setup and Operation Server Configuration Client Authentication Database Roles Managing Databases Localization Routine Database Maintenance Tasks Backup and Restore High Availability, Load Balancing, and Replication Recovery Configuration Monitoring Database Activity Monitoring Disk Usage Reliability and the Write-Ahead Log Regression Tests Client Interfaces libpq - C Library Large Objects ECPG - Embedded SQL in C The Information Schema Server Programming Extending SQL Triggers The Rule System Procedural Languages PL/pgSQL - SQL Procedural Language PL/Tcl - Tcl Procedural Language PL/Perl - Perl Procedural Language PL/Python - Python Procedural Language Server Programming Interface Internals Overview of PostgreSQL Internals System Catalogs Frontend/Backend Protocol PostgreSQL Coding Conventions Native Language Support Writing A Procedural Language Handler Writing A Foreign Data Wrapper Genetic Query Optimizer Index Access Method Interface Definition GiST Indexes GIN Indexes Database Physical Storage BKI Backend Interface How the Planner Uses Statistics
osqlint Oracle SQL Intermediate 14 hours Audience All who want to improve their basic skills in Oracle SQL and also systematize already gained knowledge. Format of the course 25% lectures, 75% labs Create complex queries to databases Use available operators Queries with multiple conditions Creating tables and references DDL commands (create, alter, and drop) Create referential integrity Normalization of tables (up to 3 normal form) anomalies and ways to avoid them Changes in the structure of existing tables ALTER clause Manipulation of data DML commands (insert, update, delete) Creating new users and granting permissions DCL commands (grant, revoke) Linking Tables Internal and external joins Data Aggregation Features of grouping functions Use the GROUP BY clause and HAVING Grouping multiple column Subqueries multi-column correlated WITH clause
453 Oracle: (1ZO-147) Program with PLSQL 28 hours Overview of PL/SQL Programs Describe a PL/SQL program construct List the components of a PL/SQL block List the benefits of subprograms Describe how a stored procedure/function is invoked Creating Procedures Define what a stored procedure is List the development steps for creating a procedure Create a procedure Describe the difference between formal and actual parameters List the types of parameter modes List the methods for calling a procedure with parameters Describe the DEFAULT option for parameters Create a procedure with parameters Invoke a procedure that has parameters Define a subprogram in the declarative section of a procedure Describe how exceptions are propagated Remove a procedure Creating Functions Define what a stored function is Create a function List how a function can be invoked List the advantages of user-defined functions in SQL statements List where user-defined functions can be called from within an SQL statement Describe the restrictions on calling functions from SQL statements Remove a function Describe the differences between procedures and functions Managing Subprograms Contrast system privileges with object privileges Grant privileges Contrast invokers rights with definers rights Identify views in the data dictionary to manage stored objects Creating Packages Use DESCRIBE command to describe packages and list their possible components Identify a package specification and body Create packages: Create related variables , cursors, constants, exceptions, procedures, and functions Designate a package construct as either public or private Invoke a package construct Use a bodiless package Drop Packages Identify benefits of Packages More Package Concepts Write packages that use the overloading feature Use Forward Referencing Describe errors with mutually referential subprograms Initialize variables with a one-time-only procedure Identify persistent states in package variables and cursors Identify restrictions on using Packaged functions in SQL statements Invoke packaged functions from SQL Use PL/SQL tables and records in Packages Oracle Supplied Packages Describe the benefits of Execute Immediate over DBMS_SQL for Native Dynamic SQL Identify the flow of execution Use EXECUTE IMMEDIATE Describe the use and application of some Oracle server-supplied packages: DBMS_SQL, DBMS_OUTPUT, UTL_FILE Manipulating Large Objects Compare and contrast LONG and large object (LOB) data types Describe LOB datatypes and how they are used Differentiate between internal and external LOBs Identify and Manage Bfiles Migrate from LONG To LOB Use the DBMS_LOB PL/SQL package Create LOB columns and populate them Perform SQL operations on LOBS: Update LOBs with SQL, Select from LOBS, Delete LOBS Describe the use of temporary LOBs Creating Database Triggers Describe the different types of triggers Describe database triggers and their uses List guidelines for designing triggers Create a DML trigger List the DML trigger components Describe the trigger firing sequence options Use conditional predicates in a DML trigger Create a row level trigger Create a statement level trigger Use the OLD and NEW qualifiers in a database trigger Create an INSTEAD OF trigger Describe the difference between stored procedures and triggers Describe the trigger execution model Alter a trigger status Remove a trigger More Trigger Concepts Define what a database trigger is Describe events that cause database triggers to fire Create a trigger for a DDL statement Create a trigger for a system event Describe the functionality of the CALL statement Describe the cause of a mutating table List what triggers can be implemented for List the privileges associated with triggers View trigger information in the dictionary views Managing Dependencies Track procedural dependencies Describe dependent objects and referenced objects View dependency information in the dictionary views Describe how the UTLDTREE script is used Describe how the IDEPTREE and DEPTREE procedures are used Describe a remote dependency List how remote dependencies are governed Describe when a remote dependency is unsuccessfully recompiled Describe when a remote dependency is successfully recompiled List how to minimize dependency failures
mongodbau MongoDB for Advanced Users 14 hours This course covers the advanced areas in the use of programming languages related to MongoDB, the goal is for the participant to have the ability to completely master the tool.   Advanced Data Manipulations Adjustment of the Mongo Shell Efficient handling CRUD operations (inserts, queries, updates, deletes) Useful admin commands Performance optimization Built in monitoring tools: mongotop, mongostat Analysing memory and IO performance MongoDB Cloud Manager and Munin Identifying sub-optimal queries. Using the query profiler. Storage engines: MMAPv1 and WiredTiger Explainable object Indexing and special collections Managing indexes and MongoDB indexing internals Single field and compound indexes Indexes on arrays and sub-documents Geo Indexes Capped collections, TTL and tailable cursors Aggregation  Single purpose aggregation Aggregation pipelines Introduction to map-reduce Replication How asynchronous replication works in MongoDB Setting-up and maintaining replica set Using write concern and read preference Handling replication failures Sharding How auto sharding works Setting up a MongoDB shard cluster How to wisely choose a shard key Advanced administering a sharded cluster Managing unbalanced sharded cluster Dealing with chunks (splitting, merging, migrating Security Authentication and authorization in replica sets and sharded clusters Managing privileges and custom roles Recommendations for secure deployment Backup and Restore Plans filesystem based strategies mongodump and mongorestore point-in-time recovery
seqdba SequoiaDB for Administrators 14 hours SequoiaDB is a document-oriented NewSQL database that supports JSON transaction processing and SQL query. SequoiaDB can directly interface with applications to provide high performance and horizontally scalable data storage and processing functions, or serve as the frontend to Hadoop and Spark for both real-time query and data analysis. Using SequoiaDB Starting SequoiaDB Connectors (Hadoop/Hive/Map Reduce) Basic Operators with reference Administrating SequoiaDB Database Management Replication Cluster Reference Operator SequoiaDB Shell SQL to SequoiaDB mapping list Error List
ADSQL SQL Advanced 14 hours Students will learn advanced queries and how to add, update, and delete data, tables, views, and indexes. Lesson 1: Querying with unions and advanced joins Querying multiple tables with unions Advanced Joins Calculating with COMPUTE Lesson 2: Querying with subqueries Subqueries Lesson 3: Adding data Inserting data SELECT INTO Lesson 4: Updating and removing data Updating records Deleting records Deleting the contents of tables Lesson 5: Manipulating tables and views Creating tables Modifying tables Deleting tables Adding and removing views Lesson 6: Manipulating indexes Adding and removing indexes Lesson 7: Ensuring data integrity with transactions Transactions Lesson 8: Creating databases Creating a database with SQL Deleting a database
BigData_ A practical introduction to Data Analysis and Big Data 35 hours Participants who complete this training will gain a practical, real-world understanding of Big Data and its related technologies, methodologies and tools. Participants will have the opportunity to put this knowledge into practice through hands-on exercises. Group interaction and instructor feedback make up an important component of the class. The course starts with an introduction to elemental concepts of Big Data, then progresses into the programming languages and methodologies used to perform Data Analysis. Finally, we discuss the tools and infrastructure that enable Big Data storage, Distributed Processing, and Scalability. Audience Developers / programmers IT consultants Format of the course Part lecture, part discussion, hands-on practice and implementation, occasional quizing to measure progress. Introduction to Data Analysis and Big Data What makes Big Data "big"? Velocity, Volume, Variety, Veracity (VVVV) Limits to traditional Data Processing Distributed Processing Statistical Analysis Types of Machine Learning Analysis Data Visualization Languages used for Data Analysis R language Why R for Data Analysis? Data manipulation, calculation and graphical display Python Why Python for Data Analysis? Manipulating, processing, cleaning, and crunching data Approaches to Data Analysis Statistical Analysis Time Series analysis Forecasting with Correlation and Regression models Inferential Statistics (estimating) Descriptive Statistics in Big Data sets (e.g. calculating mean) Machine Learning Supervised vs unsupervised learning Classification and clustering Estimating cost of specific methods Filtering Natural Language Processing Processing text Understaing meaning of the text Automatic text generation Sentiment analysis / Topic analysis Computer Vision Acquiring, processing, analyzing, and understanding images Reconstructing, interpreting and understanding 3D scenes Using image data to make decisions Big Data infrastructure Data Storage Relational databases (SQL) MySQL Postgres Oracle Non-relational databases (NoSQL) Cassandra MongoDB Neo4js Understanding the nuances Hierarchical databases Object-oriented databases Document-oriented databases Graph-oriented databases Other Distributed Processing Hadoop HDFS as a distributed filesystem MapReduce for distributed processing Spark All-in-one in-memory cluster computing framework for large-scale data processing Structured streaming Spark SQL Machine Learning libraries: MLlib Graph processing with GraphX Scalability Public cloud AWS, Google, Aliyun, etc. Private cloud OpenStack, Cloud Foundry, etc. Auto-scalability Choosing the right solution for the problem The future of Big Data Closing remarks
gfsjeeint Administering GlassFish Server with Java EE applications introduction 21 hours Introduction to GlassFish Server Overview of the Java EE Architecture GlassFish Background GlassFish Basic Architecture GlassFish Basic Features Installing and upgrading Installation Upgrade Administering and deploying applications Administration High Availability Administration Security Application Deployment Message Queue Administration Troubleshooting Troubleshooting Error Message Scaling and tuning the performance Deployment Planning Performance Tuning Developing applications Your First Cup: An Introduction to the Java EE Platform The Java EE Tutorial Application Development Guide Message Queue Developer's Guide for Java Clients Message Queue Developer's Guide for JMX Clients Message Queue Developer's Guide for C Clients Extending and embedding Add-On Component Development Guide Embedded Server Guide
surveyp Research Survey Processing 28 hours This four day course walks you from the point you design your research surveys to the tme where you gather and collect the findings of the survey. The course is based on Excel and Matlab. You will learn how to design the survey form and what the suitable data fields should be, and how to process extra data information when needed. The course will show you the way the data is entered and how to validate and correct wrong data values. At the end the data analysis will be conducted in a variety of ways to ensure the effectiveness of the data gathered and to find out hidden trends and knowledge within this data. A number of case studies will be carried out during the course to make sure all the concepts have been well understood.Day 1: Data analysis Determining the Target of the survey Survey Design data fields and their types dealing with drill down surveies Data Collection Data Entry Excel Session Day 2: Data cleaning Data reduction Data Sampling Removing unexpcted data Removing outlier Data Analysis statstics is not enough Excel Session Day 3: Data visualization parallel cooridnates scatter plot pivot tables cross tables Excel Session Conducting data mining algorithms on the data Decision tree Clustering mining assoiciation rules matlab session Day 4: Reporting and Disseminating Results Archiving data and the finding out Feedback for conducting new surveies
452 R12.x Extend Oracle Applications: Building OA Framework Applications 35 hours Introduction to OA Framework Agenda Important Terminology Foundation Knowledge Additional Resources Concepts of the MVC Design Pattern JSPs and OA Framework Concepts of the Model Concepts of the View Concepts of the Controller Basics of the Model BC4J Model Applications Modules Entity Objects View Objects Other BC4J Objects BC4J Database Interactions Basics of the View View-layer Components Workspaces and Projects Pages and Regions Items CSS Styles Attributes Sets Basics of the Controller Handling GETs Handling POSTs Common Controller tasks Lab
osqldevdm Oracle SQL for development and database management 35 hours Database Development Recapping the basic principles behind relational databases Concepts and terminology      Retrieving data using the SELECT statement Using simple and more complex JOINS to retrieve data from multiple tables SELF, INNER and OUTER joins Restricting and sorting data, conditional expressions Single row functions: string, date and time manipulation IF-THEN-ELSE statements Conversion of data between types Creating aggregated reports Using correlated and uncorrelated subqueries in SELECT statements Retrieving and manipulating data using subqueries Running Data Manipulation Statements in Oracle to manage database transactions Query optimisation and efficiency Database Management The Oracle Data Dictionary: introduction and usage Creating views, indexes, constraints and synonyms Controlling and revoking user access to schema objects (tables, views) Managing indexes and constraints
percsera Administrating Percona Server for MongoDB 7 hours Percona Server for MongoDB is a free, enhanced, fully compatible, open source, drop-in replacement for MongoDB 3.2 Community Edition with enterprise-grade features. It requires no changes to MongoDB applications or code. Audience This course is suitable for sysadmins and engineers seeking to switch to Percona Server from preexisting MongoDB instances, or deploy and administrate new Percona Server for MongoDB instances. After completing this course, delegates will: understand Percona Server’s structure and deployment mechanisms be able to carry out installation / production environment / architecture tasks and configuration be able to assess code quality, perform debugging, monitoring be able to implement advanced production like replication, performance tuning and logging Getting Started Installing Percona Server for MongoDB Percona FT Storage Engine Switching Storage Engines Configuring PerconaFT External Authentication Overview External Authentication Commands Environment Setup and Configuration Percona TokuBackup Architectural Overview Making a Backup Checking Backup Progress Controlling Backup Rate Restoring From Backup Creating New Replicas Sharding Auditing    
cassadmin Cassandra Administration 14 hours This course will introduce Cassandra –  a popular NoSQL database.  It will cover Cassandra principles, architecture and data model.   Students will learn data modeling  in CQL (Cassandra Query Language) in hands-on, interactive labs.  This session also discusses Cassandra internals and some admin topics. Section 1: Introduction to Big Data / NoSQL NoSQL overview CAP theorem When is NoSQL appropriate Columnar storage NoSQL ecosystem Section 2 : Cassandra Basics Design and architecture Cassandra nodes, clusters, datacenters Keyspaces, tables, rows and columns Partitioning, replication, tokens Quorum and consistency levels Labs : interacting with cassandra using CQLSH Section 3: Data Modeling – part 1 introduction to CQL CQL Datatypes creating keyspaces & tables Choosing columns and types Choosing primary keys Data layout for rows and columns Time to live (TTL) Querying with CQL CQL updates Collections (list / map / set) Labs : various data modeling exercises using CQL ; experimenting with queries and supported data types Section 4: Data Modeling – part 2 Creating and using secondary indexes composite keys (partition keys and clustering keys) Time series data Best practices for time series data Counters Lightweight transactions (LWT) Labs : creating and using indexes;  modeling time series data Section 5 : Cassandra Internals understand Cassandra design under the hood sstables, memtables, commit log Section 6: Administration Hardware selection Cassandra distributions Cassandra Nodes Communication Writing and Reading data to/from the storage engine Data directories Anti-entropy operations Cassandra Compaction Choosing and Implementing compaction strategies Cassandra best practices (compaction, garbage collection,) troubleshooting tools and tips Lab : students install Cassandra, run benchmarks
mariadbadmin MariaDB Database Administration 14 hours MariaDB Administration training course is for anyone who wants to administrate the MariaDB database server. It is a comprehensive course covering all administrator duties. The course explains how MariaDB Database works, what tools are available, how we can use them, how we can secure the MariaDB Database Server and configure it. During the training course you will learn how to manage user accounts and how the MariaDB Access Privilege System works. You also will learn how to maintain your database, backup and recover your databases and perform crash recovery. Installing MariaDB server Installing in Ubuntu/Debian Installing in other Linux Distributions Installation on Windows MariaDB Server Files and Scripts MariaDB Programs MariaDB Server MariaDB Client GUI Tools MariaDB Server Configuration Server Options The Server SQL Mode Server System Variables Dynamic System Variables Server Status Variables Shutdown Process MariaDB Security Issues Securing MariaDB Against Attacks Security-Related Options Security Issues with LOAD DATA LOCAL MariaDB Access Privilege System MariaDB Privilege System Overview Privileges Provided by MariaDB Connecting to the MariaDB Server - Stages Access Control, Stage 1: Connection Verification Access Control, Stage 2: Request Verification Access Denied Errors MariaDB User Account Management Users and Passwords Creating New Users Deleting User Accounts Limiting User Resources Changing Passwords MariaDB Database Maintenance Backup and Recovery Point-in-Time Recovery Maintenance and Crash Recovery myisamchk Syntax and Options Getting Table Information MariaDB Local Setting National Characters and Sorting MariaDB Server Time Zone MariaDB Log Files Error Log General Query Log Update Log Binary Log Slow Query Log Log File Maintenance and Rotation Running Multiple MariaDB Servers on the Same Machine Running Multiple Servers in Windows Running Multiple Servers in Windows as Services Running Multiple Servers in Unix and Linux Using Client Tools in a Multi-Server Environment MariaDB Query Cache The Concept of Query Cache Testing Query Cache with SELECT Configuring Query Cache Checking Query Cache Status and Maintenance The CONNECT Storage Engine Installing the CONNECT storage engine Creating and dropping CONNECT tables Reading and writing CSV data using CONNECT Reading and writing XML data using CONNECT Accessing MariaDB tables using CONNECT Using the XCOL table type Using the PIVOT table type Using the OCCUR table type Exploring Dynamic and Virtual Columns in MariaDB Creating tables with dynamic columns Inserting, updating, and deleting dynamic column data Reading data from a dynamic column Using virtual columns Performance and Usage Statistics Installing the Audit Plugin Using the Audit Plugin Using engine-independent table statistics Using extended statistics Enabling the performance schema Using the performance schema Optimizing and Tuning MariaDB Using SHOW STATUS Controlling MariaDB optimizer strategies Using extended Keys with InnoDB and XtraDB Configuring the MyISAM segmented key cache Configuring threadpool Configuring the Aria pagecache Optimizing queries with the subquery cache Optimizing semijoin subqueries Using microseconds in DATETIME columns Updating the DATETIME and TIMESTAMP columns automatically  
transsqladv Transact SQL Advanced 7 hours Delegates will gain an understanding of some of the more advanced features of Transact SQL as well as being able to do each of the following: Use queries to return complex result sets Manage database objects to aid query performance Tune queries to perform more efficiently This course is for anyone who currently uses Transact SQL to extract data from a Microsoft SQL Server database and wishes to expand their knowledge particularly in the areas of data analysis and improving query speed. Analytical Functions Use of advanced summary functions Use of hierarchical queries Use of analytical summary functions, e.g. moving averages, running totals Use of ranking functions Useful Database Objects Principles of using indexes How to create and maintain an index Use of clustered tables Use of partitioned tables Use of metadata in the master database Query Performance Tracing Principles of query execution and optimisation Use of Execution Plan Use of table & index statistics Use of hints Basic Data Warehouse Techniques Use of Indexed Views Use of Dimension & fact tables Use of Star & Snowflake designs
68403 Introduction to SQL Server 2012 Integration Services (SSIS) 28 hours ETL and SSIS Packages Control Flow Workflow Constraints Data Flows Variables Containers Transactions Errors and Debugging Logging Slowly Changing Dimensions Deploying a Package Security Scripting Best Practices
378 Oracle Service Bus 11g - Design and Integration 21 hours This course is targeted to SOA architects and developers. It consists of theory classes and hands-on sessions on each of the topics to cover all essential features of Oracle Service Bus 11g. This course will be delivered by industry experts with vast knowledge of Oracle SOA Suite, Web services, ESB, XML, SOA and related topics for example Java/J2EE. Introduction to Oracle Service Bus Installation Oracle XE and OSB 11g Creation of Domain OSB Console Oracle Mediator vs OSB Session Management in OSB Console Creation of Project, Folder Business Service, Proxy Service configuration Testing of Business and Proxy Service Message Context, Predefined Message Context Variables Routing, Conditional Branching, Operational Branching Routing Table Publishing Log, Report, Alert actions Transformation using XPath and XQuery Transport Header action Service callout Java Callout Validation Split-Join Dynamic Routing/ Publishing Service virtualization Security Service Pooling
cpd200 CPD200: Developing Solutions on Google Cloud Platform 24 hours This 3 day instructor-led class introduces participants to Solution Development for Google Cloud Platform. Through a combination of instructor-led presentations, demonstrations, and hands-on labs, students learn how to develop cloud-based applications using Google App Engine, Google Cloud Datastore, and Google Cloud Endpoints. This class is intended for experienced application developers who want to learn how to develop solutions using Google Cloud Platform to create highly scalable backends for both web and mobile applications. At the end of this one­day course, participants will be able to: Manage Google Cloud Source Repositories using the Google Cloud Platform Console Test an App Engine application using the App Engine SDK Access the App Engine Development Server Console Create an API using Google Cloud Endpoints Test a Cloud Endpoint API using the API Explorer Deploy an application to App Engine using the App Engine SDK Design, structure and configure an App Engine application using multiple services Create Client IDs using the Google Cloud Platform Console Secure App Engine services and Cloud Endpoints APIs using authentication Configure and upload new versions of App Engine services Integrate Google Cloud Logging into App Engine applications Review quota usage in a Google Cloud Platform project Integrate different types of storage with App Engine applications Create and implement a data model for use with Google Cloud Datastore Implement a variety of queries in Google Cloud Datastore Update the index configuration in Google Cloud Datastore Implement transactions using Google Cloud Datastore Review Google Cloud Trace reports in the Google Cloud Platform Console Integrate the Memcache API into an App Engine application to increase performance Configure, run and review the output of Google Cloud Security Scanner Configure the scaling behaviour of individual App Engine Services Create App Engine handlers for Push Task Queues Send email from an App Engine application using the Mail API Schedule Tasks in App Engine using the Cron Service Update the configuration of the Cron Service Secure Task Push, and Cron Service handlers  Export Google Cloud Platform data from a project Delete Google Cloud Platform projects and resources   Module 1: Developing Solutions for Google Cloud Platform Identify the advantages of Google Cloud Platform for solution development Identify services and tools available for solution development using Google Cloud Platform Compare examples of Google Cloud Platform architectures for solution development Lab: Google Cloud Source Repositories Create a project for the course Use Google Cloud Shell to develop and test an application using the App Engine SDK  Configure Google Cloud Source Repositories to remotely host code in Google Cloud Platform Module 2: Google Cloud Endpoints Identify Cloud Endpoints features Explain how to develop APIs using Cloud Endpoints Compare development of Cloud Endpoints APIs using Java and Python Lab: Google Cloud Endpoints Review and edit Cloud Endpoints source code Deploy an application to App Engine Test a Cloud Endpoints  API in the APIs Explorer Module 3: App Engine Services Explain the use cases for App Engine Services and how to use them in structuring an application Identify how to deploy and access individual App Engine services Explain how to route requests to individual services Lab: Google App Engine Services Review the code for a sample application used throughout the remainder of the course Deploy multiple App Engine services to a single project Module 4: User Authentication and Credentials Compare authentication and authorization Identify options for securing App Engine applications Explain the use cases for Application Default Credentials Lab: User Authentication Configure the OAuth consent screen and create a client ID Modify Conference Central to use your client ID Test Conference Central authentication Modify your admin service to require administrator rights Module 5: Managing App Engine Applications Explain the use cases for App Engine versions Identify how to access App Engine monitoring and logging services Explain the use of resource quotas and how to troubleshoot related errors Lab: Managing Google App Engine Applications Review App Engine settings, quotas, instances, and logs Update App Engine services to log to Cloud Logging Deploy new versions of your default and admin services Route all traffic to a new version of the default service Module 6: Storage for Solution Developers Compare storage options for App Engine Solutions Developers Explain the purpose of, and use cases for, Google Cloud Storage Compare Cloud SQL integration with App Engine and Compute Engine Explain basic Cloud Datastore terminology and concepts, including Entity Groups Lab: Google Cloud Datastore Update an existing application to save data persistently Test saving application data to Cloud Datastore List and view Cloud Datastore entities in the Google Cloud Platform Console Module 7: Queries and Indexes Identify available query filters for Cloud Datastore Compare single­property, and composite indexes in Cloud Datastore Configure and optimize indexes for Cloud Datastore Lab: Google Cloud Datastore Queries and Indexes Add support for querying entities by kind and ancestor Add query filters to Cloud Datastore searches Update an index configuration to support composite indexes Module 8: Entity Groups, Consistency, and Transactions Identify the steps of a Cloud Datastore write Compare strong and eventual consistency in Cloud Datastore Identify how to achieve strongly consistent queries Identify best practises for Cloud Datastore transactions Lab: Google Cloud Datastore Transactions Add support for using Cloud Datastore transactions to an application Add a Cloud Endpoint API method to view data from a different service Module 9: App Engine Performance and Optimization Identify Memcache types, use cases, and implementation patterns Compare available scaling behaviours for application services Configure application scaling for individual services Lab: Google App Engine Performance and Optimization Review Cloud Trace reports for an application Configure and run a security scan for an application Update an application to make use of memcache Configure and test application scaling for application services Module 10: Task Queues Compare Push and Pull Queues Explain how to schedule tasks with the Cron Service Configure and securing Push and Pull Queues, as well as the Cron Service Lab: Task Queue API Add a task handler to send an email using the Mail API Add a Cron Service handler and configuration to an existing application Lab: Deleting Google Cloud Platform Projects and Resources Export Google Cloud Platform data from a project Delete Google Cloud Platform resources Shut down a Google Cloud Platform project
TalendDI Talend Open Studio for Data Integration 28 hours Talend Open Studio for Data Integration is an open-source data integration product used to combine, convert and update data in various locations across a business. In this instructor-led, live training, participants will learn how to use the Talend ETL tool to carry out data transformation, data extraction, and connectivity with Hadoop, Hive, and Pig.   By the end of this training, participants will be able to Explain the concepts behind ETL (Extract, Transform, Load) and propagation Define ETL methods and ETL tools to connect with Hadoop Efficiently amass, retrieve, digest, consume, transform and shape big data in accordance to business requirements Audience Business intelligence professionals Project managers Database professionals SQL Developers ETL Developers Solution architects Data architects Data warehousing professionals System administrators and integrators Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us.  
fsharpfordatascience F# for Data Science 21 hours Data science is the application of statistical analysis, machine learning, data visualization and programming for the purpose of understanding and interpreting real-world data. F# is a well suited programming language for data science as it combines efficient execution, REPL-scripting, powerful libraries and scalable data integration. In this instructor-led, live training, participants will learn how to use F# to solve a series of real-world data science problems. By the end of this training, participants will be able to: Use F#'s integrated data science packages Use F# to interoperate with other languages and platforms, including Excel, R, Matlab, and Python Use the Deedle package to solve time series problems Carry out advanced analysis with minimal lines of production-quality code Understand how functional programming is a natural fit for scientific and big data computations Access and visualize data with F# Apply F# for machine learning Explore solutions for problems in domains such as business intelligence and social gaming Audience Developers Data scientists Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us.
osqlbgn Oracle SQL for beginners 21 hours Listeners This training is addressed for people starting to work with the SQL language in Oracle database The course answer for questions: How to build a query? What possibilities have SQL? What is a relational database? What is the structure and SQL commands Relational database models The structure of a relational database Connection types of tables The normalization and denormalization database Relational Operators Download the data Rules for writing SQL queries The syntax for the SELECT Selecting all columns Inquiries from arithmetic operations Aliases columns Literals Concatenation operator Limiting results The WHERE clause Comparison operators LIKE Condition Prerequisite BETWEEN ... AND IS NULL condition Condition IN Boolean operators AND, OR and NOT Many of the conditions in the WHERE clause The order of the operators. DISTINCT clause Sorting Data The ORDER BY clause Sorting by multiple columns or expressions SQL functions The differences between the functions of one and multilines Features text, numeric, date, Explicit and implicit conversion Conversion functions Nesting functions Viewing the performance of the functions - dual table Getting the current date function SYSDATE Handling of NULL values Aggregating data using the grouping Grouping functions How grouping functions treat NULL values Create groups of data - the GROUP BY clause Grouping multiple columns Limiting the function result grouping - the HAVING clause Retrieving data from multiple tables Types of connectors The use NATURAL JOIN Aliases tables Joins in the WHERE clause INNER JOIN Inner join External Merge LEFT, RIGHT, FULL OUTER JOIN Cartesian product Subqueries Place subqueries in the SELECT command Subqueries single and multi-lineage Operators Subqueries single-line Features grouping in subquery Operators Subqueries multi-IN, ALL, ANY How NULL values ​​are treated in subqueries Operators collective UNION operator UNION ALL operator INTERSECT operator MINUS operator Insert, update, and delete data INSERT command Copy data from another table UPDATE command DELETE command TRUNCATE command Transactions Commands COMMIT, ROLLBACK, and SAVEPOINT DDL commands The main database objects Rules for naming objects Creating tables The data types available for columns DEFAULT option Option NULL and NOT NULL Managing tables Referential integrity CHECK, PRIMARY KEY, FOREIGN KEY, UNIQUE Create a table by the query Delete a table DROP TABLE DESCRIBE command Other schema objects Sequences Synonyms Views
osqladv Oracle SQL Advanced 14 hours Listeners This course is designed for people who want to use the advanced features of SQL in Oracle The course answers the questions How to build advanced queries? How to create advanced reports? Control user access User Management System permissions and object Granting Receiving permission Roles Using the links Managing schema objects ALTER TABLE command Adding, modifying, and deleting columns Add, remove, turn off constraintów Create indexes Flashback operations External tables Operations on large data sets MERGE command DML operations of podzapytaniami DML operations with RETURNING clause INSERT command multi tables Conditional expressions CASE expression DECODE expression Generate reports by grouping related data The GROUP BY clause The HAVING clause Aggregating data - ROLLUP and CUBE operators Identification summaries - GROUPING function Aggregating data - GROUPING SETS operator Managing data in different time zones Time zones Variations TIMESTAMP Differences between DATE and TIMESTAMP Conversion operations Advanced subqueries Subqueries Multi-column subqueries The subquery in the FROM clause Correlated subqueries WITH clause - re-use query blocks Join tables Inequality in the WHERE clause and the FROM clause Semijoin Antijoin The processing of hierarchical data The tree structure hierarchical Queries Pseudo column Sort data in a hierarchical query Useful functions Regular expressions Simple and complex patterns
3057 Oracle SQL Language 14 hours The course answers questions How to build a query? What possibilities have SQL? What is a relational database? What is the structure and SQL commands Relational database models The structure of a relational database Connection types of tables The normalization and denormalization database Database Management System (RDBMS) Relational Operators Characteristics of declarative SQL language SQL Syntax Division language DQL, DML, DDL, DCL Language DQL (Data Query Language) SELECT queries Aliases columns, tables Service date (DATE types, display functions, formatting) Group Features Combining internal and external tables UNION operator Nested Subqueries (the WHERE clause, the table name, column name) Correlated subqueries Data Modification Language Inserting rows (INSERT clause) Inserting via query Updating rows (UPDATE) Removing rows (DELETE) Data Definition Language Create, change of ownership, remove tables (CREATE, ALTER, DROP) Creating tables by asking (CREATE TABLE .... AS SELECT ...) CONSTRAINTS Options NULL and NOT NULL CONSTRAINT clause Condition PRIMARY KEY Condition UNIQUE Condition FOREIGN KEY DEFAULT clause Transactions The command COMMIT, ROLLBACK, SAVEPOINT Language DCL Granting and revoking permissions (GRANT, REVOKE) Roles Creating Users sequences Synonyms The views (perspective)

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SQL in Microsoft Access - GöteborgMon, 2018-01-01 09:302820EUR / 3320EUR
Access Advanced - Stockholm, HotorhetWed, 2018-01-03 09:304160EUR / 5710EUR

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