Implementing and Maintaining Microsoft SQL Server2008 Analysis Services - 6234

Module 1: Introduction to Microsoft SQL Server Analysis Services
This module introduces common analysis scenarios and describes how Analysis Services provides a powerful platform for multidimensional OLAP solutions and data mining solutions. The module then describes the main considerations for installing Analysis Services.

Lessons

•Overview of Data Analysis Solutions
•Overview of SQL Server Analysis Services
•Installing SQL Server Analysis Services
Lab : Using SQL Server Analysis Services
•(Level 200) Installing SQL Server Analysis Services
•(Level 200) Verifying Installation

Module 2: Creating Multidimensional Analysis Solutions

This module introduces the development tools you can use to create an Analysis Services multidimensional analysis solution, and describes how to create data sources, data source views, and cubes.

Lessons
•Developing Analysis Services Solutions
•Creating Data Sources and Data Source Views
•Creating a Cube
Lab : Creating Multidimensional Analysis Solutions
•(Level 200) Creating a Data Source
•(Level 200) Creating and Modifying a Data Source View
•(Level 200) Creating and Modifying a Cube

Module 3: Working with Cubes and Dimensions

This module describes how to edit dimensions and to configure dimensions, attributes, and hierarchies.
Lessons

•Configuring Dimensions
•Defining Attribute Hierarchies
•Sorting and Grouping Attributes
Lab : Working with Cubes and Dimensions
•(Level 200) Configuring Dimensions
•(Level 200) Defining Relationships and Hierarchies
•(Level 200) Sorting and Grouping Dimension Attributes

Module 4: Working with Measures and Measure Groups

This module explains how to edit and configure measures and measure groups.

Lessons
•Working With Measures
•Working with Measure Groups
Lab : Working with Measures and Measure Groups
•(Level 200) Configuring Measures
•(Level 200) Defining Dimension Usage and Relationships
•(Level 200) Configuring Measure Group Storage

Module 5: Querying Multidimensional Analysis Solutions

This module introduces multidimensional expressions (MDX) and describes how to implement calculated members and named sets in an Analysis Services cube.

Lessons

•MDX Fundamentals
•Adding Calculations to a Cube
Lab : Querying Multidimensional Analysis Solutions
•(Level 200) Querying a Cube by Using MDX
•(Level 200) Creating a Calculated Member
•(Level 200) Defining a Named Set

Module 6: Customizing Cube Functionality

This module explains how to customize a cube by implementing key performance indicators (KPIs), actions, perspectives, and translations.

Lessons

•Implementing Key Performance Indicators
•Implementing Actions
•Implementing Perspectives
•Implementing Translations
Lab : Customizing Cube Functionality
•(Level 200) Implementing a KPI
•(Level 200) Implementing an Action
•(Level 200) Implementing a Perspective
•(Level 200) Implementing a Translation

Module 7: Deploying and Securing an Analysis Services Database

This module describes how to deploy an Analysis Services database to a production server, and how to implement security in an Analysis Services multidimensional solution.

Lessons

•Deploying an Analysis Services Database
•Securing an Analysis Services Database
Lab : Deploying and Securing an Analysis Services Database
•(Level 200) Deploying an Analysis Services Database
•(Level 200) Securing an Analysis Services Database

Module 8: Maintaining a Multidimensional Solution

This module discusses the maintenance tasks associated with an Analysis Services solution, and describes how administrators can use the Analysis Services management tools to perform them.

Lessons

•Configuring Processing
•Logging, Monitoring, and Optimizing an Analysis Services Solution
•Backing Up and Restoring an Analysis Services Database
Lab : Maintaining a Multidimensional Solution
•(Level 200) Configuring Processing
•(Level 200) Implementing Logging and Monitoring
•(Level 200) Backing Up and Restoring an Analysis Services Database

Module 9: Introduction to Data Mining

This module introduces data mining, and describes how to implement data mining structures and models. It then explains how to validate data model accuracy.

Lessons

•Overview of Data Mining
•Creating a Data Mining Solution
•Validating Data Mining Models
Lab : Introduction to Data Mining
•(Level 200) Creating a Data Mining Structure
•(Level 200) Adding a Data Mining Model
•(Level 200) Exploring Data Mining Models
•(Level 200) Validating Data Mining Models
 
Before attending this course, students must have: Conceptual understanding of OLAP solutions. Experience navigating the Microsoft Windows Server environment. Experience with Windows services (starting and stopping). Experience creating service accounts and permissions. Experience with Microsoft SQL Server, including: SQL Server Agent. SQL Server query language (SELECT, UPDATE, INSERT, and DELETE). SQL Server System tables. SQL Server accounts (users and permissions).