Summary
In this chapter on data warehousing in the cloud, we covered key concepts and approaches to data warehousing, including the normalized approach by Bill Inmon and the dimensional approach by Ralph Kimball. We also explored building a data warehouse in the cloud using Azure SQL Database and Synapse SQL, including dedicated pools and serverless pools with the medallion architecture.
By the end of this chapter, readers should have a solid understanding of the different data warehousing approaches and the benefits of building a data warehouse in the cloud. They should also be able to build a data warehouse using Azure SQL Database and Synapse SQL. These skills are essential for data architects looking to design and implement data warehousing solutions in the cloud.
The semantic layer is the next logical step in building a data platform after the data warehouse. It enables users to easily access and analyze data without needing to understand the complex underlying data model...
