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SQL Server 2014 Business Intelligence: Integration Services and Analysis Services (Canada)
Hands-On Technology Transfer


Delivery Method
Seminar
Seminar

Target Audience
Microsoft SQL Server 2014 Administrators

Summary
This hands-on course focuses on the Integration Services (SSIS) and Analysis Services (SSAS) business intelligence tools that are bundled with SQL Server 2014.

Description/Agenda

This hands-on course focuses on the Integration Services (SSIS) and Analysis Services (SSAS) business intelligence tools that are bundled with SQL Server 2014. Students will install and configure SQL Server 2014 servers that are enabled for SSIS and SSAS, which are then used for comprehensive hands on exercises demonstrating key features of SSIS/SSAS.

Students work with complex SSIS data migration projects that import/export data between multiple formats including: Access, SQL Server, Oracle and other databases, XML files, Excel spreadsheets and flat files. Also demonstrated are SSIS tasks that can download from FTP Servers, copy/move files and folders, execute Win32 processes and .NET scripts, perform bulk imports, perform database maintenance, contact (via text or e-mail) administrators, and transfer database components between SQL Servers. Error handling options are also demonstrated with hands-on exercises, as well as how to use variables and input parameters in SSIS routines. The course provides thorough coverage of how to deploy, automate, secure and troubleshoot SSIS routines.

Students will learn how to use SSAS to design, build and populate data warehouses to stage data for use by data cubes, and will perform hands-on exercises to design and build a data warehouse. Advanced data warehouse concepts, such as surrogate keys and rapidly changing dimensions are also reviewed. Subsequent exercises use SSAS to create data cubes and analyze them. Cube customization options are demonstrated, including how to add Key Performance Indicators (KPIs), custom calculations, and actions that link to SSRS reports. Attendees also learn how to optimize cube performance by defining attribute relationships and custom aggregation levels.

The course also includes an overview of data mining and the tools available to do this in SSAS, supported by a hands-on exercise that walks through the process of defining a data mining structure to predict future sales. Administration topics related to data cubes are covered, including exercises that deploy and secure cubes, process and manage cubes.

Students who are also interested in Reporting Services (SSRS) should consider the 3-day SQL Server 2014 Reporting Services course in addition to this course. An 8-day training pass is available for $3,590.

Students who are also interested in Reporting Services (SSRS) should consider the 3-day SQL Server 2014 Reporting Service course in addition to this course. An 8-day training pass is available for $3,590.

Course Prerequisites: Familiarity with database concepts, Windows desktop navigation and software installation techniques. Attendance at HOTT's SQL Programming course or Microsoft Transact-SQL Programming course is highly recommended although not required.


What You Will Learn

  • Creating Data Migration Routines with SSIS
  • Moving Data Between Databases, XML, Excel, .NET, and Flat File Formats
  • Implementing Error Handling in SSIS
  • Using Variables and Parameters in SSIS Routines
  • Deploying and Scheduling SSIS Routines
  • Designing and Building Data Warehouses
  • Populating Data Warehouses from Source Systems
  • Creating Data Cubes in SSAS
  • Adding Key Performance Indicators to Cubes
  • Adding Custom Calculations to Cubes
  • Applying Custom Formatting to Cube Data
  • Customizing Dimensions, Attributes and Hierarchies
  • Defining Attribute Relationships to Optimize Cube Performance
  • Deploying and Managing Cubes
  • Connecting to Data Cubes from Excel and Other Clients


Workshop Agenda

Installing SQL Server Business Intelligence Tools
  • Installation Requirements
  • Steps to Install SSRS, SSIS and SSAS
  • Navigating the SQL Server Data Tools Development Environment
  • New Features to SQL Server 2014 Business Intelligence
Integration Services Architecture
  • Architecture of the SSIS Data Engine
  • Using Data Transformation Tasks
  • Managing Connections to Sources and Destinations
  • ADO.NET Data Source and Destination
  • Understanding Data Buffers
  • Control Flow Tasks and Containers
Common SSIS Tasks
  • Executing SQL Statements
  • Connecting to FTP Servers
  • Sending E-mail
  • Notifying Administrators of Errors
  • Completing Bulk Inserts
  • Copying, Moving and Deleting Files and Folders
Data Transformations
  • Converting Data Types
  • Merging Data from Multiple Sources
  • Splitting Data to Multiple Destinations
  • Counting Rows
  • Sampling and Sorting Records
  • Copying Columns
Advanced SSIS Tasks
  • Executing .NET Scripts and Win32 Processes
  • Using the Windows Management Instrumentation (WMI) Tasks
  • Performing Database Maintenance and Backups During SSIS Routines
  • Using Variables and Input Parameters
  • Profiling Database Tables
  • Comparing XML Files Against Schemas
Advanced Data Transformations
  • Filling in Missing Data with Lookups
  • Locating Near Duplicate Rows with Fuzzy Grouping
  • Adding Audit Information to Results
  • Counting the Occurrence of Keywords
  • Sending Rows That Process Correctly and Incorrectly to Different Destinations
  • Respond to Truncation Errors
Migrating SQL Server 2000 DTS Packages
  • Using the Upgrade Advisor
  • Running Legacy DTS Packages on SQL Server 2005
  • Migration DTS Packages to SSIS
  • Customizing Upgraded DTS Packages
SSIS Administration and Automation
  • Deploying SSIS Routines
  • Manually Running SSIS Routines
  • Automating SSIS Execution
  • Configuring Notifications for Execution Success, Failure or Both
  • SSIS Security
  • Troubleshooting Techniques
OLAP Design
  • Understanding Fact and Dimension Tables
  • Modeling Slowly Changing and Rapidly Changing Dimensions
  • Modeling Fact Tables
  • Using Star and Snowflake Schemas for Dimension Tables
  • Implementing Surrogate Keys
  • Defining Business Keys
Creating and Populating Data Warehouses
  • Creating Data Warehouses (OLAP Databases)
  • Adding Fact Tables
  • Adding Dimension Tables and Joining Them to Fact Tables
  • Loading Data into Fact and Dimension Tables
  • Validation Techniques for Data Loads
Creating and Managing Cubes
  • Creating Data Sources to Connect to Data Warehouses
  • Using SSAS to Create Cubes
  • Applying Friendly Names to Measures and Attributes
  • Customizing Dimensions and Measures
  • Setting up Navigational Hierarchies
  • Optimizing Cubes with Attribute Relationships
Customizing Cubes
  • Adding Key Performance Indicators (KPIs)
  • Customizing Dimensions and Attributes
  • Adding Translations to Support Multiple Languages
  • Adding Custom Calculations
  • Subdividing Cubes Using Perspectives
Cube Deployment and Administration
  • Cube Storage Calculations
  • Configuring Desired Aggregation
  • Configuring Caching
  • Deploying and Processing Cubes
  • Connecting to Cubes from Excel and Other Clients
  • Partitioning and Processing Cubes
  • Backup and Restore Options
  • Securing Cubes
Multidimensional (MDX) Essentials
  • Using MDX Queries to Pull Data from Cubes
  • Understanding Tuples and Sets
  • MDX Expressions vs. Queries
  • Grouping Attribute Values into Named Sets
  • Adding Custom Calculations for Cubes Using MDX
MDX Functions
  • Using MDX Aggregate Functions
  • Using Navigations Functions to Move Though Hierarchies
  • Grouping, Filtering and Sorting Functions
  • Time-Based MDX Functions
Understanding the Data Mining Process
  • Types of Business Analysis Supported by Data Mining
  • Data Mining Process Explained
  • Understanding the Key Components of Data Mining
  • Built-In Data Mining Algorithms
  • Matching Mining Algorithms to Business Needs
Working with Data Mining Structures
  • Adding Data Mining Structures
  • Mining for Hidden Information
  • Discovering Patterns in Data
  • Creating Predictive Models
  • Using the Data Mining Wizard
  • Modifying Mining Structures with the Data Mining Designer

 

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