SQL Server Training

SQL Server Training

Implementing and Maintaining Microsoft SQL Server 2008 Analysis Services

Microsoft 6234

Microsoft Certification
Length: 3 Day(s)  
Published: December 10, 2008 (in development)  
Language(s): English  
Audience(s): IT Professionals  
Level: 200  
Technology: Microsoft SQL Server 2008  
Type: Course  
Delivery Method: Instructor-led (classroom)

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).
In addition, it is recommended, but not required, that students have completed:
  • Course 6231: Maintaining a Microsoft SQL Server 2008 Database.
  • Course 6232: Implementing a Microsoft SQL Server 2008 Database.

About this Course

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.
Audience Profile
The primary audience for this course is individuals who design and maintain business intelligence solutions for their organization. These individuals work in environments where databases play a key role in their primary job and may perform database administration and maintenance as part of their primary job responsibilities.
The secondary audience for this course is individuals who develop applications that deliver content from SQL Server Analysis Services to the organization.
At Course Completion
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 and cubes 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.
Course OutlineModule 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
  • Installing SQL Server Analysis Services
  • Verifying Installation
After completing this module, students will be able to:
  • 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
  • Creating a Data Source
  • Creating and Modifying a Data Source View
  • Creating and Modifying a Cube
After completing this module, students will be able to:
  • 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
  • Configuring Dimensions
  • Defining Relationships and Hierarchies
  • Sorting and Grouping Dimension Attributes
After completing this module, students will be able to:
  • 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
  • Configuring Measures
  • Defining Dimension Usage and Relationships
  • Configuring Measure Group Storage
After completing this module, students will be able to:
  • 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
  • Querying a Cube by Using MDX
  • Creating a Calculated Member
  • Defining a Named Set
After completing this module, students will be able to:
  • 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 (KPI)
  • Implementing Actions
  • Working with Perspectives
  • Working with Translations
Lab : Customizing Cube Functionality
  • Implementing a KPI
  • Implementing an Action
  • Implementing a Perspective
  • Implementing a Translation
After completing this module, students will be able to:
  • 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
  • Deploying an Analysis Services Database
  • Securing an Analysis Services Database
After completing this module, students will be able to:
  • 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
  • Configuring Processing
  • Implementing Logging and Monitoring
  • Backing Up and Restoring an Analysis Services Database
After completing this module, students will be able to:
  • 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
  • Creating a Data Mining Structure
  • Adding a Data Mining Model
  • Exploring Data Mining Models
  • Validating Data Mining Models
After completing this module, students will be able to:
  • Describe data mining.
  • Create a data mining solution.
  • Validate data mining models.

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