This three-day instructor-led course teaches students how to implement an Analysis Services solution in an organization. The course discusses how to use the Analysis Services development tools to create an Analysis Services database and an OLAP cube, and how to use the Analysis Services management and administrative tools to manage an Analysis Services solution.

What You'll Learn

After completing this course, students will be able to:

• Describe how SQL Server Analysis Services can be used to implement analytical solutions.
• Create multidimensional analysis solutions with SQL Server Analysis Services.
• Implement dimensions in an Analysis Services solution.
• Implement measures and measure groups in an Analysis Services solution.
• Query a multidimensional Analysis Services solution.
• Customize an Analysis Services cube.
• Deploy and Secure an Analysis Services database.
• Maintain a multidimensional Analysis Services solution.
• Implement a Data Mining solution.

Who Needs to Attend

This course is intended for information technology (IT) professionals and developers who need to implement analysis solutions by using Microsoft SQL Server 2005 Analysis Services.

Prerequisites

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).

Follow-On Courses

There are no follow-ons for this course.

Course Outline

1. Introduction to Microsoft SQL Server 2005 Analysis Services

• Overview of Data Analysis Solutions
• Overview of SQL Server 2005 Analysis Services
• Installing SQL Server 2005 Analysis Services

2. Creating Multidimensional Analysis Solutions

• Developing Analysis Services Solutions
• Data Sources and Data Source Views
• Creating a Cube

3. Working with Dimensions

• Configuring Dimensions
• Defining Hierarchies
• Sorting and Grouping Attributes

4. Working with Measures and Measure Groups

• Working with Measures
• Working with Measure Groups

5. Querying Multidimensional Analysis Solutions

• MDX Fundamentals
• Adding Calculations to a Cube

6. Customizing Cube Functionality

• Implementing Key Performance Indicators
• Implementing Actions
• Implementing Perspectives
• Implementing Translations

7. Deploying and Securing an Analysis Services Database

• Deploying an Analysis Services Database
• Securing an Analysis Services Database

8. Maintaining a Multidimensional Solution

• Configuring Processing Settings
• Logging, Monitoring, and Optimizing an Analysis Services Solution
• Backing Up and Restoring an Analysis Services Database

9. Introduction to Data Mining

• Overview of Data Mining
• Creating a Data Mining Solution
• Validating Data Mining Models

Labs

1. Install SQL Server 2005 Analysis Services.

2. Creating a Multidimensional Analysis Solution

• Creating a Data Source
• Creating and Modifying a Data Source View
• Creating and Modifying a Cube

3. Defining Dimensions

• Configuring Dimensions
• Defining Relationships and Hierarchies
• Sorting and Grouping Dimension Attributes

4. Configuring Measures and Measure Groups

• Configuring Measures
• Defining Dimension Usage and Relationships
• Configuring Measure Group Storage

5. Querying a Cube

• Querying a Cube by Using MDX
• Creating a Calculated Member
• Defining a Named Set

6. Customizing a Cube

• Implementing a KPI
• Implementing an Action
• Implementing a Perspective
• Implementing a Translation

7. Deploying and Securing an Analysis Services Database

• Deploying an Analysis Services Database
• Securing an Analysis Services Database

8. Maintaining an Analysis Services Database

• Configuring Processing
• Implementing Logging and Monitoring
• Backing Up and Restoring an Analysis Services Database

9. Implementing Data Mining

• Creating a Data Mining Structure
• Adding a Data Mining Model
• Exploring Data Mining Models
• Validating Data Mining Models