Implementing
and Maintaining Microsoft SQL Server2008 Analysis Services
Course 6234A: Three days; Instructor-Led
Introduction
Elements of this syllabus
are subject to change.
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.
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.
After completing this
course, students will be able to:
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• |
Describe how SQL Server
Analysis Services can be used to implement analytical solutions. |
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Create multidimensional
analysis solutions with SQL Server Analysis Services. |
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• |
Implement dimensions and
cubes in an Analysis Services solution. |
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• |
Implement measures and
measure groups in an Analysis Services solution. |
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• |
Query a multidimensional
Analysis Services solution. |
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• |
Customize an Analysis
Services cube. |
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• |
Deploy and secure an
Analysis Services database. |
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• |
Maintain a
multidimensional Analysis Services solution. |
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• |
Implement a Data Mining
solution. |
Before attending this
course, students must have:
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Conceptual understanding
of OLAP solutions. |
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• |
Experience navigating
the Microsoft Windows Server environment. |
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• |
Experience with Windows
services (starting and stopping). |
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• |
Experience creating
service accounts and permissions. |
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Experience with
Microsoft SQL Server, including: |
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• |
SQL Server Agent. |
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• |
SQL Server query
language (SELECT, UPDATE, INSERT, and DELETE). |
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• |
SQL Server System
tables. |
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SQL Server accounts
(users and permissions). |
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
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Lesson 1: Overview of
Data Analysis Solutions |
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• |
Lesson 2: Overview of
SQL Server Analysis Services |
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Lesson 3: Installing SQL
Server Analysis Services |
Lab: Using SQL Server
Analysis Services
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Exercise 1: (Level 200)
Installing SQL Server Analysis Services |
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• |
Exercise 2: (Level 200)
Verifying Installation |
After completing this
module, students will be able to:
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• |
Describe data analysis
solutions. |
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• |
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
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• |
Lesson 1: Developing
Analysis Services Solutions |
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• |
Lesson 2: Creating Data
Sources and Data Source Views |
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• |
Lesson 3: Creating a
Cube |
Lab: Creating
Multidimensional Analysis Solutions
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• |
Exercise 1: (Level 200)
Creating a Data Source |
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• |
Exercise 2: (Level 200)
Creating and Modifying a Data Source View |
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• |
Exercise 3: (Level 200)
Creating and Modifying a Cube |
After completing this
module, students will be able to:
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• |
Develop Analysis
Services solutions. |
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• |
Create a data source and
a data source view. |
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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
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• |
Lesson 1: Configuring
Dimensions |
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• |
Lesson 2: Defining
Attribute Hierarchies |
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• |
Lesson 3: Sorting and
Grouping Attributes |
Lab: Working with Cubes
and Dimensions
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• |
Exercise 1: (Level 200)
Configuring Dimensions |
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• |
Exercise 2: (Level 200)
Defining Relationships and Hierarchies |
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• |
Exercise 3: (Level 200)
Sorting and Grouping Dimension Attributes |
After completing this
module, students will be able to:
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• |
Configure dimensions. |
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• |
Define hierarchies. |
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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
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Lesson 1: Working With
Measures |
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Lesson 2: Working with
Measure Groups |
Lab: Working with Measures
and Measure Groups
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• |
Exercise 1: (Level 200)
Configuring Measures |
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• |
Exercise 2: (Level 200)
Defining Dimension Usage and Relationships |
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Exercise 3: (Level 200)
Configuring Measure Group Storage |
After completing this
module, students will be able to:
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• |
Work with measures. |
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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
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• |
Lesson 1: MDX
Fundamentals |
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Lesson 2: Adding
Calculations to a Cube |
Lab: Querying
Multidimensional Analysis Solutions
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Exercise 1: (Level 200)
Querying a Cube by Using MDX |
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Exercise 2: (Level 200)
Creating a Calculated Member |
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Exercise 3: (Level 200)
Defining a Named Set |
After completing this
module, students will be able to:
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• |
Describe
Multidimensional Expression (MDX) fundamentals. |
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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
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Lesson 1: Implementing
Key Performance Indicators |
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Lesson 2: Implementing
Actions |
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Lesson 3: Implementing
Perspectives |
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Lesson 4: Implementing
Translations |
Lab: Customizing Cube
Functionality
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Exercise 1: (Level 200)
Implementing a KPI |
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Exercise 2: (Level 200)
Implementing an Action |
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Exercise 3: (Level 200)
Implementing a Perspective |
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Exercise 4: (Level 200)
Implementing a Translation |
After completing this
module, students will be able to:
|
• |
Implement Key
Performance Indicators (KPIs). |
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• |
Implement actions. |
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• |
Implement perspectives. |
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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
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Lesson 1: Deploying an
Analysis Services Database |
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• |
Lesson 2: Securing an
Analysis Services Database |
Lab: Deploying and
Securing an Analysis Services Database
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Exercise 1: (Level 200)
Deploying an Analysis Services Database |
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Exercise 2: (Level 200)
Securing an Analysis Services Database |
After completing this
module, students will be able to:
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• |
Deploy an Analysis
Services database. |
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• |
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
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Lesson 1: Configuring
Processing |
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Lesson 2: Logging, Monitoring,
and Optimizing an Analysis Services Solution |
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Lesson 3: Backing Up and
Restoring an Analysis Services Database |
Lab: Maintaining a
Multidimensional Solution
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Exercise 1: (Level 200)
Configuring Processing |
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Exercise 2: (Level 200)
Implementing Logging and Monitoring |
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Exercise 3: (Level 200)
Backing Up and Restoring an Analysis Services Database |
After completing this
module, students will be able to:
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• |
Configure processing
settings. |
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• |
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
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Lesson 1: Overview of
Data Mining |
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Lesson 2: Creating a
Data Mining Solution |
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Lesson 3: Validating
Data Mining Models |
Lab: Introduction to Data
Mining
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Exercise 1: (Level 200)
Creating a Data Mining Structure |
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Exercise 2: (Level 200)
Adding a Data Mining Model |
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Exercise 3: (Level 200)
Exploring Data Mining Models |
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Exercise 4: (Level 200)
Validating Data Mining Models |
After completing this
module, students will be able to:
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• |
Describe data mining. |
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Create a data mining
solution. |
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Validate data mining
models. |
Solutient
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Rockside Road, Suite 100 – Cleveland, OH
44131
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