Implementing and Maintaining Microsoft SQL Server 2005 Analysis Services

BI2791 : 4 Day Instructor-Led Workshop

Cubes, Data Mining, Best Practices - Learn SQL Server Analysis Services

An Interface Exclusive Combination Course of Microsoft Curriculum 2791

Deliverables:
Attendees receive the following items when taking this course:

  • Microsoft courseware 2791 (Implementing and Maintaining Microsoft® SQL Server™ 2005 Analysis Services)
  • Microsoft SQL Server(TM) 2005 Analysis Services Step by Step Book
  • Certificate of Achievements for 2791

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 2005 Analysis Services. SQL Server 2005 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.

This class incorporates a case study. 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 students the ability to exercise the skills they learned during the class in a real world situation. The courseware includes a copy of Microsoft Press Book SQL Server Analysis Services Step-by-Step.

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,Developing with SQL Server 2000/2005 Transact-SQL.

Audience:

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.

Topics Covered:

  • Introduction to Microsoft SQL Server 2005 Analysis Services
  • Creating Multidimensional Analysis Solution
  • Working with Dimensions
  • Working with Measures and Measure Groups
  • Querying Multidimensional Analysis Solutions
  • Customizing Cube Functionality
  • Maintaining a Multidimensional Solution
  • Introduction to Data Mining
  • Analysis Service Case Study

Course Outline:

Module 1: Introduction to Microsoft SQL Server 2005 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 2005 Analysis Services
  •  
  • Installing SQL Server 2005 Analysis Services
  • After completing this module, students will be able to:
  • Describe data analysis solutions.
  • Describe the key features of SQL Server 2005 Analysis Services.
  • Install SQL Server 2005 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 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
  • 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 Dimensions

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

Lessons

  • Configuring Dimensions
  • Defining 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
  • 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 4: Configuring Measures and Measure Groups

  • Exercise 1: Configuring Measures
  • Exercise 2: Defining Dimension Usage and Relationships
  • Exercise 3: 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 5: Querying a Cube

  • Exercise 1: Querying a Cube by Using MDX
  • Exercise 2: Creating a Calculated Member
  • Exercise 3: 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
  • 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
  • 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 7: Deploying and Securing an Analysis Services Database

  • Exercise 1: Deploying an Analysis Services Database
  • Exercise 2: 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 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
  • 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 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
  • After completing this module, students will be able to:
  • Describe data mining.
  • Create a data mining solution.
  • Validate 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. While working in a team environment, the student will have an opportunity to exercise the skills learned during the class.
  • After completing this module, students will be able to:
  • 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.

Exams:

70-445: TS: Microsoft SQL Server 2005 Business Intelligence Implementation and Maintenance