Course Content

Module 1 : Introduction to Business Intelligence and Data Modeling

This module introduces key BI concepts and the Microsoft BI product suite.

Lessons

• Introduction to Business Intelligence
• The Microsoft business intelligence platform

Lab : Exploring a Data Warehouse

After completing this module, you will be able to:

• Describe the concept of business intelligence
• Describe the Microsoft business intelligence platform

 

Module 2 : Creating Multidimensional Database

This module describes the steps required to create a multidimensional database with analysis services.

Lessons

• Introduction to multidimensional analysis
• Creating data sources and data source views
• Creating a cube
• Overview of cube security

Lab : Creating a multidimensional database

After completing this module, you will be able to:

• Use multidimensional analysis
• Create data sources and data source views
• Create a cube
• Describe cube security

 

Module 3 : Working with Cubes and Dimensions

This module describes how to implement dimensions in a cube.

Lessons

• Configuring dimensions
• Define attribute hierarchies
• Sorting and grouping attributes

Lab : Working with Cubes and Dimensions

After completing this module, you will be able to:

• Configure dimensions
• Define attribute hierarchies.
• Sort and group attributes

 

Module 4 : Working with Measures and Measures Groups

This module describes how to implement measures and measure groups in a cube.

Lessons

• Working with measures
• Working with measure groups

Lab : Configuring Measures and Measure Groups

After completing this module, you will be able to:

• Work with measures
• Work with measure groups

 

Module 5 : Introduction to MDX

This module describes the MDX syntax and how to use MDX.

Lessons

• MDX fundamentals
• Adding calculations to a cube
• Using MDX to query a cube

Lab : Using MDX

After completing this module, you will be able to:

• Describe the fundamentals of MDX
• Add calculations to a cube
• Query a cube using MDX

 

Module 6 : Customising Cube Functionality 

This module describes how to customize a cube.

Lessons

• Implementing key performance indicators
• Implementing actions
• Implementing perspectives
• Implementing translations

Lab : Customizing a Cube

After completing this module, you will be able to:

• Implement key performance indicators
• Implement actions
• Implement perspectives
• Implement translations

 

Module 7 : Implementing a Tabular Data Model by Using Analysis Services

This module describes how to implement a tabular data model in PowerPivot.

Lessons

• Introduction to tabular data models
• Creating a tabular data model
• Using an analysis services tabular model in an enterprise BI solution

Lab : Working with an Analysis services tabular data model

After completing this module, you will be able to:

• Describe tabular data models
• Create a tabular data model
• Be able to use an analysis services tabular data model in an enterprise BI solution

 

Module 8 : Introduction to Data Analysis Expression (DAX)

This module describes how to use DAX to create measures and calculated columns in a tabular data model.

Lessons

• DAX fundamentals
• Using DAX to create calculated columns and measures in a tabular data model

Lab : Creating Calculated Columns and Measures by using DAX

After completing this module, you will be able to:

• Describe the fundamentals of DAX
• Use DAX to create calculated columns and measures in a tabular data model

 

Module 9 : Performing Predictive Analysis with Data Mining 

This module describes how to use data mining for predictive analysis.

Lessons

• Overview of data mining
• Using the data mining add-in for Excel
• Creating a custom data mining solution
• Validating a data mining model
• Connecting to and consuming a data mining model

Lab : Perform Predictive Analysis with Data Mining

After completing this module, you will be able to:

• Describe data mining
• Use the data mining add-in for Excel
• Create a custom data mining solution
• Validate a data mining solution
• Connect to and consume a data mining solution