Implementing a SQL Data Warehouse

Live Classroom
Duration: 5 days
Live Virtual Classroom
Duration: 5 days
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During this five-day course, participants are equipped with the knowledge and skills required for provisioning a Microsoft SQL Server database. The course also discusses SQL Server provision both on-premises and in Azure, as well as installation from new and migration from an existing installs. The course is immensely helpful for database professionals who are required to step into and fulfill a business intelligence developer role.


What You'll Learn

  • 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


  • Overview of Data Warehousing
  • Considerations for a Data Warehouse Solution
  • Lab: Exploring a Data Warehouse Solution
    • Exploring data sources
    • Exploring an ETL process
    • Exploring a data warehouse

  • Considerations for data warehouse infrastructure.
  • Planning data warehouse hardware.
  • Lab: Planning Data Warehouse Infrastructure
    • Planning data warehouse hardware

  • Data warehouse design overview
  • Designing dimension tables
  • Designing fact tables
  • Physical Design for a Data Warehouse
  • Lab: Implementing a Data Warehouse Schema
    • Implementing a star schema
    • Implementing a snowflake schema
    • Implementing a time dimension table

  • Introduction to Columnstore Indexes
  • Creating Columnstore Indexes
  • Working with Columnstore Indexes
  • Lab: Using Columnstore Indexes
    • Create a Columnstore index on the FactProductInventory table
    • Create a Columnstore index on the FactInternetSales table
    • Create a memory optimized Columnstore table

  • 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 Warehouse
    • Create an Azure SQL data warehouse database
    • Migrate to an Azure SQL Data warehouse database
    • Copy data with the Azure data factory

  • Introduction to ETL with SSIS
  • Exploring Source Data
  • Implementing Data Flow
  • Lab: Implementing Data Flow in an SSIS Package
    • Exploring source data
    • Transferring data by using a data row task
    • Using transformation components in a data row

  • Introduction to Control Flow
  • Creating Dynamic Packages
  • Using Containers
  • Managing consistency.
  • Lab: Implementing Control Flow in an SSIS Package
    • Using tasks and precedence in a control flow
    • Using variables and parameters
    • Using containers
  • Lab: Using Transactions and Checkpoints
    • Using transactions
    • Using checkpoints

  • Debugging an SSIS Package
  • Logging SSIS Package Events
  • Handling Errors in an SSIS Package
  • Lab: Debugging and Troubleshooting an SSIS Package
    • Debugging an SSIS package
    • Logging SSIS package execution
    • Implementing an event handler
    • Handling errors in data flow

  • Introduction to Incremental ETL
  • Extracting Modified Data
  • Loading modified data
  • Temporal Tables
  • Lab: Extracting Modified Data
    • Using a datetime column to incrementally extract data
    • Using change data capture
    • Using the CDC control task
    • Using change tracking
  • Lab: Loading a data warehouse
    • Loading data from CDC output tables
    • Using a lookup transformation to insert or update dimension data
    • Implementing a slowly changing dimension
    • Using the merge statement

  • Introduction to Data Quality
  • Using Data Quality Services to Cleanse Data
  • Using Data Quality Services to Match Data
  • Lab: Cleansing Data
    • Creating a DQS knowledge base
    • Using a DQS project to cleanse data
    • Using DQS in an SSIS package
  • Lab: De-duplicating Data
    • Creating a matching policy
    • Using a DS project to match data

  • Introduction to Master Data Services
  • Implementing a Master Data Services Model
  • Hierarchies and collections
  • Creating a Master Data Hub
  • Lab: Implementing Master Data Services
    • Creating a master data services model
    • Using the master data services add-in for Excel
    • Enforcing business rules
    • Loading data into a model
    • Consuming master data services data

  • Using scripting in SSIS
  • Using custom components in SSIS
  • Lab: Using scripts
    • Using a script task

  • Overview of SSIS Deployment
  • Deploying SSIS Projects
  • Planning SSIS Package Execution
  • Lab: Deploying and Configuring SSIS Packages
    • Creating an SSIS catalog
    • Deploying an SSIS project
    • Creating environments for an SSIS solution
    • Running an SSIS package in SQL server management studio
    • Scheduling SSIS packages with SQL server agent

  • Introduction to Business Intelligence
  • An Introduction to Data Analysis
  • Introduction to reporting
  • Analyzing Data with Azure SQL Data Warehouse
  • Lab: Using a data warehouse
    • Exploring a reporting services report
    • Exploring a PowerPivot workbook
    • Exploring a power view report
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Who should attend

The course is highly recommended for –

  • SQL business intelligence developers
  • Data warehouse administrators
  • Data warehousing architects
  • Data engineers
  • Data architects
  • Data warehouse developers
  • Business analysts

ETL developers


Participants need to have basic knowledge of Microsoft Windows operating system and its core functionality, working knowledge of relational databases as well as have some experience with database design.

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