Audience
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
Prerequisites
Before attending this course, students must have experience of querying data using Transact-SQL.
Duration
3 days. Hands on.
Course Objectives
The focus of this 3-day instructor-led course is on creating managed enterprise BI solutions. It describes how to implement both multidimensional and tabular data models and how to create cubes, dimensions, measures, and measure groups. This course helps you prepare for the Exam 70-768.
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
Course Content
Module 1: Introduction to Business Intelligence and Data Modeling
Introduction to Business Intelligence
The Microsoft business intelligence platform
Lab : Exploring a BI Solution
After completing this module, students will be able to:
• Describe BI scenarios, trends, and project roles.
• Describe the products that make up the Microsoft BI platform.
Module 2: Creating Multidimensional Databases
Introduction to Multidimensional Analysis
Data Sources and Data Source Views
Cubes
Overview of Cube Security
Configure SSAS
Monitoring SSAS
Lab : Creating a multidimensional database
After completing this module, you will be able to:
• Describe considerations for a multidimensional database.
• Create data sources and data source views.
• Create a cube
• Implement security in a multidimensional database.
• Configure SSAS to meet requirements including memory limits, NUMA and disk layout.
• Monitor SSAS performance.
Module 3: Working with Cubes and Dimensions
Configuring Dimensions
Defining Attribute Hierarchies
Implementing Sorting and Grouping Attributes
Slowly Changing Dimensions
Lab : Working with Cubes and Dimensions
After completing this module, you will be able to:
• Configure dimensions.
• Define attribute hierarchies.
• Implement sorting and grouping for attributes.
• Implement slowly changing dimensions.
Module 4: Working with Measures and Measure Groups
Working with Measures
Working with Measure Groups
Lab : Configuring Measures and Measure Groups
After completing this module, you will be able to:
• Configure measures.
• Configure measure groups.
Module 5: Introduction to MDX
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:
• Use basic MDX functions.
• Use MDX to add calculations to a cube.
• Use MDX to query a cube.
Module 6: Customizing Cube Functionality
Implementing Key Performance Indicators
Implementing Actions
Implementing Perspectives
Implementing Translations
Lab : Customizing a Cube
After completing this module, you will be able to:
• Implement KPIs in a Multidimensional database.
• Implement Actions in a Multidimensional database.
• Implement perspectives in a Multidimensional database.
• Implement translations in a Multidimensional database.
Module 7: Implementing a Tabular Data Model by Using Analysis Services
Introduction to Tabular Data Models
Creating a Tabular Data Model
Using an Analysis Services Tabular Data Model in an Enterprise BI Solution
Lab : Working with an Analysis Services Tabular Data Model
After completing this module, students will be able to:
• Describe tabular data models.
• Describe how to create a tabular data model.
• Use an Analysis Services Tabular Model in an enterprise BI solution.
Module 8: Introduction to Data Analysis Expression (DAX)
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, students will be able to:
• Describe the key features of DAX.
• Create calculated columns and measures by using DAX.
Module 9: Performing Predictive Analysis with Data Mining
Overview of Data Mining
Creating a Custom Data Mining Solution
Validating a Data Mining Model
Connecting to and Consuming a Data-Mining Model
Using the Data Mining add-in for Excel
Lab : Using Data Mining
After completing this module, students will be able to:
• Describe considerations for data mining.
• Create a data mining model.
• Validate a data mining model.
• Connect to a data-mining model.
• Use the data mining add-in for Excel.