3-day Course 6234A Outline

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

  • Describe data analysis solutions.
  • Describe the key features of SQL Server Analysis Services.
  • Install SQL Server Analysis Services.

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

  • Develop Analysis Services solutions.
  • Create a data source and a data source view.
  • Create 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

  • Configure dimensions.
  • Define hierarchies.
  • Sort and group 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

  • Work with measures.
  • Work with measure groups.

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

  • Describe Multidimensional Expression (MDX) fundamentals.
  • Add calculations to a cube.

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

  • Implement Key Performance Indicators (KPIs).
  • Implement actions.
  • Implement perspectives.
  • Implement translations.

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

  • Deploy an Analysis Services database.
  • Secure 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

  • Configure processing settings.
  • Log, monitor, and optimize an Analysis Services solution.
  • Back up and restore 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

  • Describe data mining.
  • Create a data mining solution.
  • Validate data mining models.
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