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20768-Developing SQL Data Models  Course

20768-Developing SQL Data Models Training Course

Course Description:  The Developing SQL Data Models - 20768 course is a 3-day course that is designed to teach students how to implementing multidimensional databases by using SQL Server Analysis Services (SSAS), and at creating tabular semantic data models for analysis with SSAS.

Topics covered in the course include:

  • Describing the components, architecture, and nature of a BI solution
  • Creating a multidimensional database with analysis services
  • Implementing dimensions in a cube
  • Implementing measures and measure groups in a cube
  • Using MDX syntax
  • Customizing a cube
  • Implementing a tabular database
  • Using DAX to query a tabular model
  • Using data mining for predictive analysis

Target Student:This course is designed for database professionals who fulfil a Business Intelligence (BI) developer role.

Students should possess the following experience before attending the course:

  • Working knowledge of relational database
  • Working knowledge of Transact-SQL
  • Basic experience with the Microsoft Windows operating system and its core features
  • Some database design experience

Training Dates
(Click on the course name below to view course details and full list of class dates)

20768-Developing SQL Data Models
Locations: Available Nationwide and Online
Class Date(s): 7/29/2020 - 7/31/2020
Course Fee : $1795

20768-Developing SQL Data Models
Locations: Available Nationwide and Online
Class Date(s): 8/24/2020 - 8/26/2020
Course Fee : $1795

Course Syllabus

Section 1: Introduction to Business Intelligence and Data Modeling
This section introduces key BI concepts and the Microsoft BI product suite.

Topics :
Introduction to Business Intelligence
The Microsoft business intelligence platform

Lab :
Exploring a Data Warehouse

Section 2: Creating Multidimensional Databases
This section describes the steps required to create a multidimensional database with analysis services.

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

Lab :
Creating a multidimensional database

Section 3: Working with Cubes and Dimensions
This section describes how to implement dimensions in a cube.

Topics :
Configuring dimensions
Define attribute hierarchies
Sorting and grouping attributes

Lab :
Working with Cubes and Dimensions

Section 4: Working with Measures and Measure Groups
This section describes how to implement measures and measure groups in a cube.

Topics :
Working with measures
Working with measure groups

Lab :
Configuring Measures and Measure Groups

Section 5: Introduction to MDX
This section describes the MDX syntax and how to use MDX.

Topics :
MDX fundamentals
Adding calculations to a cube
Using MDX to query a cube

Lab :
Using MDX

Section 6: Customizing Cube Functionality
This section describes how to customize a cube.

Topics :
Implementing key performance indicators
Implementing actions
Implementing perspectives
Implementing translations

Lab :
Customizing a Cube

Section 7: Implementing a Tabular Data Model by Using Analysis Services
This section describes how to implement a tabular data model in PowerPivot.

Topics :
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

Section 8: Introduction to Data Analysis Expression (DAX)
This section describes how to use DAX to create measures and calculated columns in a tabular data model.

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

Lab :
Creating Calculated Columns and Measures by using DAX

Section 9: Performing Predictive Analysis with Data Mining
This section describes how to use data mining for predictive analysis.

Topics :
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

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