SQL Server // BI6234

Implementing and Maintaining Microsoft SQL Server 2008 Analysis Services

Analysis Services in SQL 2008. Rapidly build and deploy powerful analytical solutions that enable business users to analyze business data and achieve competitive advantage.

Course Description

This 4 day course focuses on teaching IT professionals the skills and best practices required to successfully build, operate, and deploy an analytical solution using SQL Server 2008 Analysis Services. SQL Server 2008 Analysis Services (SSAS) enables IT Professionals to rapidly build and deploy powerful analytical solutions that enable business users to analyze business data and achieve competitive advantage. SSAS enables rapid application development, increases performance and functionality, and reduces the costs and complexity of operation. The case study provides the students with a real world scenario via a set of requirements. The student must design and implement their solution based on the requirements. This gives the student the ability to exercise the skills they learned during the class in a real world situation. Exams: 70-448: Microsoft SQL Server 2008, Business Intelligence Development and Maintenance

Audience

The primary audience for this course is individuals who need to design and maintain business intelligence solution 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 individual who develop applications that deliver content from SQL Server Analysis Services to the organization.

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.
  • Exposure to Visual Studio.
  • 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: 
SQL200: Introduction to Transact-SQL

What You Will Learn

After attending this course, students will be able to:
  • Identify Common analysis scenarios
  • Describe how Analysis Services provides a powerful platform for multidimensional OLAP solutions and data mining solutions
  • Considerations for installing Analysis Services
  • Identify development tools to create an Analysis Services multidimensional analysis solution
  • Describe how to create data sources, data source views, and cubes
  • Edit dimensions and configure dimensions, attributes, and hierarchies
  • Edit and configure measures and measure groups
  • Understand multidimensional expressions (MDX) and how to implement calculated members and named sets in an Analysis Services cube
  • How to customize a cube by implementing key performance indicators (KPIs)
  • How to deploy an Analysis Services database to a production server
  • Implement security in an Analysis Services multidimensional solution
  • Understanding maintenance tasks associated with an Analysis Services solution
  • How to implement data mining structures and models
  • Analysis Service Case Study

Course Outline

1. Introduction to Microsoft SQL Server 2008 Analysis Services
  • Overview of Data Analysis Solutions
  • Overview of SQL Server 2008 Analysis Services
  • Installing SQL Server 2008 Analysis Services
2. Creating Multidimensional Analysis Solutions
  • Developing Analysis Services Solutions
  • Data Sources and Data Source Views
  • Creating a Cube

    Lab 2: Creating a Multidimensional Analysis Solution
    Exercise 1: Creating a Data Source
    Exercise 2: Creating and Modifying a Data Source View
    Exercise 3: Creating and Modifying a Cube

3. Working with Dimensions

  • Configuring Dimensions
  • Defining Attribute Hierarchies
  • Sorting and Grouping Attributes

    Lab 3: Defining Dimensions
    Exercise 1: Configuring Dimensions
    Exercise 2: Defining Relationships and Hierarchies
    Exercise 3: Sorting and Grouping Dimension Attributes

4. Working with Measures and Measure Groups

  • Working with Measures
  • Working with Measure Groups

    Lab 4: Configuring Measures and Measure Groups
    Exercise 1: Configuring Measures
    Exercise 2: Defining Dimension Usage and Relationships
    Exercise 3: Configuring Measure Group Storage

5. Querying Multidimensional Analysis Solutions

  • Multidimensional Expressions (MDX) Fundamentals
  • Adding Calculations to a Cube

    Lab 5: Querying a Cube
    Exercise 1: Querying a Cube by Using MDX
    Exercise 2: Creating a Calculated Member
    Exercise 3: Defining a Named Set

6. Customizing Cube Functionality

  • Implementing Key Performance Indicators (KPIs)
  • Implementing Actions
  • Implementing Perspectives
  • Implementing Translations

    Lab 6: Customizing a Cube
    Exercise 1: Implementing a KPI
    Exercise 2: Implementing an Action
    Exercise 3: Implementing a Perspective
    Exercise 4: Implementing a Translation

7. Deploying and Securing an Analysis Services Database

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

    Lab 7: Deploying and Securing an Analysis Services Database
    Exercise 1: Deploying an Analysis Services Database
    Exercise 2: 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

    Lab 8: Maintaining an Analysis Services Database
    Exercise 1: Configuring Processing
    Exercise 2: Implementing Logging and Monitoring
    Exercise 3: 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

    Lab 9: Implementing Data Mining
    Exercise 1: Creating a Data Mining Structure
    Exercise 2: Adding a Data Mining Model
    Exercise 3: Exploring Data Mining Models
    Exercise 4: Validating Data Mining Models

Module 10: Analysis Service Case Study

This module provides the student the opportunity to build their first OLAP database solely based on user requirements.  The student will have an opportunity to exercise the skills learned during the class. 

  • Design and create an OLAP database based on user requirements.
  • Enhance the OLAP metadata to make it user friendly.
  • Deploy the OLAP database into a production environment.
  • Validate the cube structure using browser tools.