Please note: for Attend from Anywhere customers an additional screen is required. The additional screen must have a minimum screen size of 19 inch and minimum resolution of 1280x1024, with the vertical resolution 1024 being the most critical.
This three-day instructor-led course is aimed at database professionals who fulfil a Business Intelligence BI developer role. This course looks at implementing multidimensional databases by using SQL Server Analysis Services SSAS, and at creating tabular semantic data models for analysis with SSAS.
The primary audience for this course are database professionals who need to fulfil BI Developer role to create enterprise BI solutions. Primary responsibilities will include:
- Implementing multidimensional databases by using SQL Server Analysis Services
- Creating tabular semantic data models for analysis by using SQL Server Analysis Services
- The secondary audiences for this course are 'power' information workers/data analysts.
After completing this course, students will be able to:
- Describe the components, architecture, and nature of a BI solution
- Create a multidimensional database with analysis services
- Implement dimensions in a cube
- Implement measures and measure groups in a cube
- Use MDX syntax
- Customize a cube
- Implement a tabular database
- Use DAX to query a tabular model
- Use data mining for predictive analysis
Module 1: Introduction to Business Intelligence and Data Modelling
This module introduces key BI concepts and the Microsoft BI product suite.
- Introduction to Business Intelligence
- The Microsoft business intelligence platform
Lab : Exploring a Data Warehouse
Module 2: Creating Multidimensional Databases
This module describes the steps required to create a multidimensional database with analysis services.
- Introduction to multidimensional analysis
- Creating data sources and data source views
- Creating a cube
- Overview of cube security
Lab : Creating a multidimensional database
Module 3: Working with Cubes and Dimensions
This module describes how to implement dimensions in a cube.
- Configuring dimensions
- Define attribute hierarchies
- Sorting and grouping attributes
Lab : Working with Cubes and Dimensions
Module 4: Working with Measures and Measure Groups
This module describes how to implement measures and measure groups in a cube.
- Working with measures
- Working with measure groups
Lab : Configuring Measures and Measure Groups
Module 5: Introduction to MDX
This module describes the MDX syntax and how to use MDX.
- MDX fundamentals
- Adding calculations to a cube
- Using MDX to query a cube
Lab : Using MDX
Module 6: Customizing Cube Functionality
This module describes how to customize a cube.
- Implementing key performance indicators
- Implementing actions
- Implementing perspectives
- Implementing translations
Lab : Customizing a Cube
Module 7: Implementing a Tabular Data Model by Using Analysis Services
This module describes how to implement a tabular data model in PowerPivot.
- 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
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.
- DAX fundamentals
- Using DAX to create calculated columns and measures in a tabular data model
Lab : Creating Calculated Columns and Measures by using DAX
Module 9: Performing Predictive Analysis with Data Mining
This module describes how to use data mining for predictive analysis.
- 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
This course requires that you meet the following prerequisites:
- Basic knowledge of the Microsoft Windows operating system and its core functionality.
- Working knowledge of Transact-SQL.
- Working knowledge of relational databases.