The Data Warehouse ETL Toolkit: Practical Techniques for Extracting, Cleaning, Conforming, and Delivering Data

Chapter 5. Delivering Dimension Tables

Dimension tables provide the context for fact tables and hence for all the measurements presented in the data warehouse. Although dimension tables are usually much smaller than fact tables, they are the heart and soul of the data warehouse because they provide entry points to data. We often say that a data warehouse is only as good as its dimensions. We think the main mission of the ETL team is the handoff of the dimension tables and the fact tables in the delivery step, leveraging the end user applications most effectively.

Note

PROCESS CHECK Planning & Design:

Requirements/Realities → Architecture → Implementation → Test/Release Data Flow: Extract → Clean → Conform → Deliver

Chapters 5 and Chapters 6 are the pivotal elements of this book; they describe in a highly disciplined way how to deliver data to end users and their analytic applications. While there is considerable variability in the data structures and delivery-processing techniques leading up to this handoff, the final ETL step of preparing the dimensional table structures is much more constrained and disciplined.

Please keep in mind that our insistence on using these highly constrained design techniques is not adherence to a foolish consistency of a dimensional modeling methodology but rather is the key to building data warehouse systems with replicable, scalable, usable, and maintainable architectures. The more a data warehouse design deviates from these standardized dimensional modeling ...