Developing SQL Data Models 20768-C

4.5/5

Developing SQL Data Models 20768-C is designed to create 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. Moreover, this 3 days course is for database professionals who need to fulfill the 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. For this course having experience of querying data using Transact-SQL is mandatory, you will be provided with a certificate of Developing SQL Data Models by the end of the course. 

Training Options

Classroom Training

Online Instructor Led

Onsite Training

Course Information

Module 1: Introduction to Business Intelligence and Data Modeling

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

Lessons

  • Introduction to Business Intelligence
  • The Microsoft business intelligence platform

Lab : Exploring a BI Solution

  • 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

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

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Lab : Creating a multidimensional database

  • 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, 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

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 : Working with Cubes and Dimensions

  • Configuring Dimensions
  • Defining Relationships and Hierarchies
  • Sorting and Grouping Dimension Attributes

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

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

Lessons

  • Working with Measures
  • Working with Measure Groups

Lab : Configuring Measures and Measure Groups

  • Configuring Measures
  • Defining Regular Relationships
  • Configuring Measure Group Storage

After completing this module, you will be able to:

  • Configure measures.
  • Configure measure groups.

Module 5: Introduction to MDX

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 : Using MDX

  • Querying a cube using MDX
  • Adding a Calculated Member

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

This module describes how to customize a cube.

Lessons

  • Implementing Key Performance Indicators
  • Implementing Actions
  • Implementing Perspectives
  • Implementing Translations

Lab : Customizing a Cube

  • Implementing an action
  • Implementing a perspective
  • Implementing a translation

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

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 : Working with an Analysis Services Tabular Data Model

  • 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)

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 : Creating Calculated Columns and Measures by using DAX

  • 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

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 : Using Data Mining

  • 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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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
  • Creating tabular semantic data models for analysis by using SQL Server Analysis Services.

Skills gained

  • Describe the components, architecture, and nature of a BI solution
  • Create a multidimensional database with Analysis Services
  • Implement dimensions in a cube

Q: How SQL is being developed?

A: Firstly you need to install SQL Server Management Studio and then select a server and click Connect, Click on + the database server then add new Database, after naming the database click and select New Table and finally to create the Primary (int) key in the first row and that how your first SQL database will be created. 

Q: How does SQL database work?

A: For extracting and organizing data that is stored in a relational database SQL database is used. A database is a table that consists of rows and columns, SQL is the language of databases.

Q: In development, SQL is used?

A: For the Web Application Developer and Administrator, Oracle SQL Developer allows you to administer Oracle Rest Data Services and for creating and altering your RESTful services. 

Q: What are SQL data types?

A: Some of the SQL Data types are:

  • Character strings.
  • Exact numerics. 
  • Unicode character strings.
  • Approximate numerics. 
  • Binary strings.
  • Date and time. 
  • Other data types.

 

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    What People say?

    Mohammed Aljbreen Operation Specialist, SAMA

    The Clarity of the Content was very good. The explanation of the trainer with in-depth knowledge in a proper flow really impressed me to give 5 star rating.

    Arindam Chakraborty Systems Specialist, King Abdullah University of Sciences & Technology

    The Instructor was really impressive. Clear cut explanation of every topic he covered with real time scenarios.

    Sher Afzal Khan Cloud Engineer, Cloud 9 Networks

    The Trainer and the Course Material, both are good. Good flow of explanation with simple examples. The complete training was focused on current industry challenges.

    Jawed Ahmad Siddiqui Sr. System Administrator, Saudi Ceramics

    The Trainer’s presentation was impressed me to continue the course till end. Never feel bore till the entire sessions. She studied our mindset and follows.

      Mohammed Aljbreen Operation Specialist, SAMA

      The Clarity of the Content was very good. The explanation of the trainer with in-depth knowledge in a proper flow really impressed me to give 5 star rating.

      Arindam Chakraborty Systems Specialist, King Abdullah University of Sciences & Technology

      The Instructor was really impressive. Clear cut explanation of every topic he covered with real time scenarios.

      Sher Afzal Khan Cloud Engineer, Cloud 9 Networks

      The Trainer and the Course Material, both are good. Good flow of explanation with simple examples. The complete training was focused on current industry challenges.

      Jawed Ahmad Siddiqui Sr. System Administrator, Saudi Ceramics

      The Trainer’s presentation was impressed me to continue the course till end. Never feel bore till the entire sessions. She studied our mindset and follows.

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