Modeling Slowly Changing Dimensions

In Chapter 7, Putting Conceptual Modeling into Practice, we were introduced to database facts and dimensions. While facts capture the transactions of business operations, dimensions help give those transactions meaning by providing descriptive attributes, groupings, and other contextual details. Without careful curation and maintenance of dimension tables, databases would be like 1950s police dramas (just the facts, ma’am), lacking all color and making meaningful analysis impossible.

Dimensions shed light on the nature of entities in a data model, providing details such as a customer’s billing address or a product’s description. However, entity details are constantly in flux in the fast-paced business world—customers relocate, and products gain new features. A data warehouse must be able to keep up with the steady stream of changes and allow users to quickly pivot between the latest state of the world and a historical...