Course 20768-C: Developing SQL Data Models

Microsoft

Course 20768-C: Developing SQL Data Models

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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.

Audience Profile

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 and creating tabular semantic data models for analysis by using SQL Server Analysis Services.

Prerequisites

Course outline

Module 1: Introduction to Business Intelligence and Data Modeling

Module Overview

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

Lessons

Introduction to Business Intelligence
The Microsoft business intelligence platform

Lab Sessions

Exploring a BI Solution

Lab Lessons

Exploring a Data Warehouse
Exploring a data model

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

Module Overview

This module describes how to create multidimensional databases using SQL Server Analysis Services.

Lessons

Introduction to Multidimensional Analysis
Data Sources and Data Source Views
Cubes
Overview of Cube Security
Configure SSAS
Monitoring SSAS

Lab Sessions

Creating a multidimensional database

Lab Lessons

Creating a Data Source
Creating and Configuring a data Source View
Creating and Configuring a Cube
Adding a Dimension to a Cube

After completing this module, students 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

Module Overview

This module describes how to implement dimensions in a cube.

Lessons

Configuring Dimensions
Defining Attribute Hierarchies
Implementing Sorting and Grouping Attributes
Slowly Changing Dimensions

Lab Sessions

Working with Cubes and Dimensions

Lab Lessons

Configuring Dimensions
Defining Relationships and Hierarchies
Sorting and Grouping Dimension Attributes

After completing this module, students 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

Module Overview

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

Lessons

Working with Measures
Working with Measure Groups

Lab Sessions

Configuring Measures and Measure Groups

Lab Lessons

Configuring Measures
Defining Regular Relationships
Configuring Measure Group Storage

After completing this module, students will be able to:

Configure measures.
Configure measure groups.

Module 5: Introduction to MDX

Module Overview

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 Sessions

Using MDX

Lab Lessons

Querying a cube using MDX
Adding a Calculated Member

After completing this module, students 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

Module Overview

This module describes how to customize a cube.

Lessons

Implementing Key Performance Indicators
Implementing Actions
Implementing Perspectives
Implementing Translations

Lab Sessions

Customizing a Cube

Lab Lessons

Implementing an action
Implementing a perspective
Implementing a translation

After completing this module, students 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

Module Overview

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

Lessons

Introduction to Tabular Data Models
Creating a Tabular Data Model
Using an Analysis Services Tabular Data Model in an Enterprise BI Solution

Lab Sessions

Working with an Analysis Services Tabular Data Model

Lab Lessons

Creating an Analysis Services Tabular Data Model
Configure Relationships and Attributes
Configuring Data Model for an Enterprise BI Solution

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)

Module Overview

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 Sessions

Creating Calculated Columns and Measures by using DAX

Lab Lessons

Creating Calculated Columns
Creating Measures
Creating a KPI
Creating a Parent – Child Hierarchy

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

Module Overview

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

Lessons

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 Sessions

Using Data Mining

Lab Lessons

Creating a Data Mining Structure and Model
Exploring Data Mining Models
Validating Data Mining Models
Consuming a Data Mining Model
Using the Excel Data Mining add-in

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

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