20767 Implementing a SQL Data Warehouse
8/16/2021 - 8/20/2021
9/27/2021 - 10/1/2021
11/8/2021 - 11/12/2021



COURSE TIMES: 9:00am - 4:30pm

Printable version of this course
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This five-day instructor-led course provides students with the knowledge and skills to provision a Microsoft SQL Server 2016 database. The course covers SQL Server 2016 provision both on-premise and in Azure, and covers installing from new and migrating from an existing install.


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.

This course requires that you meet the following prerequisites:

  • Basic knowledge of the Microsoft Windows operating system and its core functionality.
  • Working knowledge of relational databases.
  • Some experience with database design


*Course Cost listed does not include the cost of courseware or exam. Course is subject to a minimum enrollment to run. Course may run virtually as a Virtual Instructor-Led (VILT) class if the minimum enrollment is not met. If the course is under the minimum enrollment the course may run as 4 day class (Bootcamp Style). For more information, please contact learn@vtec.org or call 207-775-0244.


Module 1: Introduction to Data Warehousing
Overview of Data Warehousing
Considerations for a Data Warehouse Solution
Lab : Exploring a Data Warehouse Solution

Module 2: Planning Data Warehouse Infrastructure
Considerations for Building a Data Warehouse
Planning data warehouse hardware.
Lab : Planning Data Warehouse Infrastructure

Module 3: Designing and Implementing a Data Warehouse
Designing dimension tables
Designing fact tables
Physical Design for a Data Warehouse
Lab : Implementing a Data Warehouse Schema

Module 4: Columnstore Indexes
Introduction to Columnstore Indexes
Creating Columnstore Indexes
Working with Columnstore Indexes
Lab : Using Columnstore Indexes

Module 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
Lab : Implementing an Azure SQL Data WarehouseCopying data with the Azure data factory

Module 6: Creating an ETL Solution
Introduction to ETL with SSIS
Exploring Source Data
Implementing Data Flow
Lab : Implementing Data Flow in an SSIS Package

Module 7: Implementing Control Flow in an SSIS Package
Introduction to Control Flow
Creating Dynamic Packages
Using Containers
Managing consistency.
Lab : Implementing Control Flow in an SSIS Package
Lab : Using Transactions and Checkpoints

Module 8: Debugging and Troubleshooting SSIS Packages
Debugging an SSIS Package
Logging SSIS Package Events
Handling Errors in an SSIS Package
Lab : Debugging and Troubleshooting an SSIS Package

Module 9: Implementing a Data Extraction Solution
Introduction to Incremental ETL
Extracting Modified Data
Loading modified data
Temporal Tables
Lab : Extracting Modified Data
Lab : Loading Incremental Changes

Module 10: Enforcing Data Quality
Introduction to Data Quality
Using Data Quality Services to Cleanse Data
Using Data Quality Services to Match Data
Lab : Cleansing Data
Lab : De-duplicating Data

Module 11: Using Master Data Services
Introduction to Master Data Services
Implementing a Master Data Services Model
Hierarchies and collections
Creating a Master Data Hub
Lab : Implementing Master Data Services

Module 12: Extending SQL Server Integration Services (SSIS)
Using Scripting in SSIS
Using custom components in SSIS
Lab : Using Scripts and Custom Components

Module 13: Deploying and Configuring SSIS Packages
Overview of SSIS Deployment
Deploying SSIS Projects
Planning SSIS Package Execution
Lab : Deploying and Configuring SSIS Packages

Module 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
Lab : Using a data warehouse