20767 Implementing a SQL Data Warehouse

Price
$2,975.00
SATV Eligible
Duration
 5 Days
Delivery Methods
 VILT    Private Group
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Note: This course is being retired by Microsoft on December 31, 2021.

This five-day instructor-led course provides students with the knowledge and skills to provision a Microsoft SQL Server database. The course covers SQL Server provision both on-premise and in Azure, and covers installing from new and migrating from an existing install.

 

Upcoming Class Dates and Times

Aug 16  - Aug 20, 2021
8:00AM - 4:00PM Central
5 Days
Virtual Instructor Led
 GTR
Enroll
Oct 04  - Oct 08, 2021
8:00AM - 4:00PM Central
5 Days
Virtual Instructor Led
 GTR
Enroll
Nov 29  - Dec 03, 2021
8:00AM - 4:00PM Central
5 Days
Virtual Instructor Led
 GTR
Enroll

Who Should Attend

The primary audience for this course are database professionals who need to fulfil a Business Intelligence Developer role. They will need to focus on hands-on work creating BI solutions including Data Warehouse implementation, ETL, and data cleansing.

Course Objectives

    After completing this course, students will be able to:
  • Describe the key elements of a data warehousing solution
  • Describe the main hardware considerations for building a data warehouse
  • Implement a logical design for a data warehouse
  • Implement a physical design for a data warehouse
  • Create columnstore indexes
  • Implementing an Azure SQL Data Warehouse
  • Describe the key features of SSIS
  • Implement a data flow by using SSIS
  • Implement control flow by using tasks and precedence constraints
  • Create dynamic packages that include variables and parameters
  • Debug SSIS packages
  • Describe the considerations for implement an ETL solution
  • Implement Data Quality Services
  • Implement a Master Data Services model
  • Describe how you can use custom components to extend SSIS
  • Deploy SSIS projects
  • Describe BI and common BI scenarios

Agenda

1 - Introduction to Data Warehousing
  • Overview of Data Warehousing
  • Considerations for a Data Warehouse Solution
2 - Planning Data Warehouse Infrastructure
  • Considerations for data warehouse infrastructure.
  • Planning data warehouse hardware.
3 - Designing and Implementing a Data Warehouse
  • Data warehouse design overview
  • Designing dimension tables
  • Designing fact tables
  • Physical Design for a Data Warehouse
4 - Columnstore Indexes
  • Introduction to Columnstore Indexes
  • Creating Columnstore Indexes
  • Working with Columnstore Indexes
5 - Implementing an Azure SQL Data Warehouse
  • Advantages of Azure SQL Data Warehouse
  • Implementing an Azure SQL Data Warehouse
  • Developing an Azure SQL Data Warehouse
  • Migrating to an Azure SQ Data Warehouse
  • Copying data with the Azure data factory
6 - Creating an ETL Solution
  • Introduction to ETL with SSIS
  • Exploring Source Data
  • Implementing Data Flow
7 - Implementing Control Flow in an SSIS Package
  • Introduction to Control Flow
  • Creating Dynamic Packages
  • Using Containers
  • Managing consistency.
8 - Debugging and Troubleshooting SSIS Packages
  • Debugging an SSIS Package
  • Logging SSIS Package Events
  • Handling Errors in an SSIS Package
9 - Implementing a Data Extraction Solution
  • Introduction to Incremental ETL
  • Extracting Modified Data
  • Loading modified data
  • Temporal Tables
10 - Enforcing Data Quality
  • Introduction to Data Quality
  • Using Data Quality Services to Cleanse Data
  • Using Data Quality Services to Match Data
11 - Using Master Data Services
  • ntroduction to Master Data Services
  • Implementing a Master Data Services Model
  • Hierarchies and collections
  • Creating a Master Data Hub
12 - Extending SQL Server Integration Services (SSIS)
  • Using scripting in SSIS
  • Using custom components in SSIS
13 - Deploying and Configuring SSIS Packages
  • Overview of SSIS Deployment
  • Deploying SSIS Projects
  • Planning SSIS Package Execution
14 - Consuming Data in a Data Warehouse
  • Introduction to Business Intelligence
  • An Introduction to Data Analysis
  • Introduction to reporting
  • Analyzing Data with Azure SQL Data Warehouse
 

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