Implementing a Data Warehouse SQL Server 2019

Create a long-term data storage solution using SQL Server 2019 and Azure SQL Data Warehouse.

Introduction

• Store information in a data warehouse
• What you should know
• Set up the example databases

1. Data Warehouse Foundations

• Data warehouse core concepts
• Transactional databases vs. data warehouses
• Dimensions and facts
• Star and snowflake schemas
• Hardware and infrastructure

2. Create a Data Warehouse

• Create a data warehouse in SQL Server
• Design dimension tables
• Design fact tables
• Create an indexed view

3. Columnstore Indexes

• Advantages of columnstore indexes
• Memory-optimized columnstore table
• Rebuild columnstore indexes

4. Implement an Azure SQL Data Warehouse

• Hosting a data warehouse in the cloud
• Create an Azure SQL Data Warehouse project
• Develop tables in Azure SQL Data Warehouse
• The Data Warehouse Migration Utility
• Migrate a data warehouse to Azure
• Pause and remove an Azure data warehouse

5. Extract, Transform, and Load (ETL)

• What is ETL and SQL Server Integration Services (SSIS)?
• Understand data flow
• Establish control flow

6. Enforce Data Quality

• SQL Server Data Quality Services (DQS)
• Cleanse data with DQS
• Create a custom knowledge base

7. Master Data Services

• Introduction to Master Data Services (MDS)
• Install MDS and IIS
• Configure Master Data Services
• Deploy a sample MDS model
• Install the MDS Excel add-in
• Update master data in Excel

8. Consume Data from the Warehouse

• Business intelligence applications

Conclusion

• Next steps