Course M20767 Implementing a SQL Data Warehouse

  • 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

After completing this course, students will be able to:

This 5-day, instructor-led course describes how to implement a data warehouse platform to support a BI solution. You will learn how to create a data warehouse with Microsoft® SQL Server® 2016 and with Azure SQL Data Warehouse, to implement ETL with SQL Server Integration Services, and to validate and cleanse data with SQL Server Data Quality Services and SQL Server Master Data Services.

Audience Profile

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.


Before attending this course, students must have:
  • At least 2 years’ experience of working with relational databases, including:
  • Designing a normalized database.
  • Creating tables and relationships.
  • Querying with Transact-SQL.
  • Some exposure to basic programming constructs (such as looping and branching).
  • An awareness of key business priorities such as revenue, profitability, and financial accounting is desirable.
Module 1: Introduction to Data Warehousing
  • Overview of Data Warehousing
  • Considerations for a Data Warehouse Solution
Module 2: Planning Data Warehouse Infrastructure
  • Considerations for Building a Data Warehouse
  • Data Warehouse Reference Architectures and Appliances
Module 3: Designing and Implementing a Data Warehouse
  • Logical Design for a Data Warehouse
  • Physical Design for a Data Warehouse
Module 4: Columnstore Indexes
  • Introduction to Columnstore Indexes
  • Creating Columnstore Indexes
  • Working with 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
Module 6: Creating an ETL Solution
  • Introduction to ETL with SSIS
  • Exploring Source Data
  • Implementing Data Flow
Module 7: Implementing Control Flow in an SSIS Package
  • Introduction to Control Flow
  • Creating Dynamic Packages
  • Using Containers
Module 8: Debugging and Troubleshooting SSIS Packages
  • Debugging an SSIS Package
  • Logging SSIS Package Events
  • Handling Errors in an SSIS Package
Module 9: Implementing an Incremental ETL Process
  • Introduction to Incremental ETL
  • Extracting Modified Data
  • Temporal Tables
Module 10: Enforcing Data Quality
  • Introduction to Data Quality
  • Using Data Quality Services to Cleanse Data
  • Using Data Quality Services to Match Data
Module 11: Using Master Data Services
  • Master Data Services Concepts
  • Implementing a Master Data Services Model
  • Managing Master Data
  • Creating a Master Data Hub
Module 12: Extending SQL Server Integration Services (SSIS)
  • Using Custom Components in SSIS
  • Using Scripting in SSIS
Module 13: Deploying and Configuring SSIS Packages
  • Overview of SSIS Deployment
  • Deploying SSIS Projects
  • Planning SSIS Package Execution
Module 14: Consuming Data in a Data Warehouse
  • Introduction to Business Intelligence
  • Introduction to Reporting
  • An Introduction to Data Analysis
  • Analyzing Data with Azure SQL Data Warehouse

Labs

  • Exploring a Data Warehouse Solution
  • Planning Data Warehouse Infrastructure
  • Implementing a Data Warehouse Schema
  • Using Columnstore Indexes
  • Implementing an Azure SQL Data Warehouse
  • Implementing Data Flow in an SSIS Package
  • Implementing Control Flow in an SSIS Package
  • Using Transactions and Checkpoints
  • Debugging and Troubleshooting an SSIS Package
  • Extracting Modified DataLab : Loading Incremental Changes
  • Cleansing DataLab : De-duplicating Data
  • Implementing Master Data Services
  • Using Scripts and Custom Components
  • Deploying and Configuring SSIS Packages
  • Using Business Intelligence Tools

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Course Code

M20767

Length, days (hours)

5 (40)

Closest dates

Price, UAH