Developing SQL Data Models (M20768)

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.

This course incorporates material from the Official Microsoft Learning Product 20768: Developing SQL Data Models

    Aug 2 2021

    Date: 08/02/2021 - 08/04/2021 (Monday - Wednesday) | 8:30 AM - 4:30 PM (EST)
    Location: ONLINE (Virtual Classroom Live)
    Delivery Format: VIRTUAL CLASSROOM LIVE Request Quote & Enroll

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    Developing SQL Data Models (M20768)

    August 2 - 4, 2021 | 8:30 AM - 4:30 PM (EST) | Virtual Classroom Live


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    Oct 25 2021

    Date: 10/25/2021 - 10/27/2021 (Monday - Wednesday) | 8:30 AM - 4:30 PM (EST)
    Location: ONLINE (Virtual Classroom Live)
    Delivery Format: VIRTUAL CLASSROOM LIVE Request Quote & Enroll

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    Developing SQL Data Models (M20768)

    October 25 - 27, 2021 | 8:30 AM - 4:30 PM (EST) | Virtual Classroom Live


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    Nov 29 2021

    Date: 11/29/2021 - 12/01/2021 (Monday - Wednesday) | 8:30 AM - 4:30 PM (EST)
    Location: ONLINE (Virtual Classroom Live)
    Delivery Format: VIRTUAL CLASSROOM LIVE Request Quote & Enroll

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    Developing SQL Data Models (M20768)

    November 29 - December 1, 2021 | 8:30 AM - 4:30 PM (EST) | Virtual Classroom Live


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1. Introduction to Business Intelligence and Data Modeling

  • Introduction to Business Intelligence
  • Microsoft Business Intelligence Platform

2. Create Multidimensional Databases

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

3. Working Cubes and Dimensions

  • Configure Dimensions
  • Define Attribute Hierarchies
  • Implementing Sorting and Grouping Attributes
  • Slowly Changing Dimensions

4. Working with Measures and Measure Groups

  • Working with Measures
  • Working with Measure Groups

5. Introduction to Multidimensional Expressions (MDX)

  • MDX Fundamentals
  • Add Calculations to a Cube
  • Use MDX to Query a Cube

6. Customize Cube Functionality

  • Implement Key Performance Indicators
  • Implement Actions
  • ImplementPerspectives
  • Implement Translations

7. Implement a Tabular Data Model by Using Analysis Services

  • Introduction to Tabular Data Models
  • Create a Tabular Data Model
  • Use an Analysis Services Tabular Model in an Enterprise BI Solution

8. Introduction to Data Analysis Expression (DAX)

  • DAX Fundamentals
  • Using Dax to create Calculated Columns and Measures in a Tabular Data Model

9. Perform Predictive Analysis with Data Mining

  • Overview of Data Mining
  • Create a Custom Data Mining Solution
  • Validate a Data Mining Model
  • Connecting to and Consume a Data Mining Model
  • Using the Data Mining add-in for Excel

*Please Note: Course Outline is subject to change without notice. Exact course outline will be provided at time of registration.
  • 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

Lab 1: Exploring a BI Solution
Lab 2: Create a Multidimensional Database
Lab 3: Work with Cubes and Dimensions
Lab 4: Configure Measures and Groups
Lab 5: Use MDX
Lab 6: Customize a Cube
Lab 7: Working with an Analysis Services Tabular Data Model
Lab 8: Create Calculated Columns and Measures using DAX
Lab 9: Using Data Mining

  • Basic knowledge of the Microsoft Windows operating system and its core functionality.
  • Experience of querying data usingTransact-SQL.
  • Data analysts and power information workers
  • Database professionals who fulfill a BI developer role and create enterprise BI solutions and whose primary responsibilities include:
    • Implementing multidimensional databases by using SSAS
    • Creating tabular semantic data models for analysis by using SSAS

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