Stars, tables, and activities: How do we model the real world? | Census

The Data Warehouse Toolkit, written by Ralph Kimball and Margy Ross, has been the mainstream method of data modeling for 25 years, providing a framework for dimensional models, star schemas, and fact and dimension tables. The basic organization of separate tables makes sense to most people, and it's easy to join them together, but some argue that this approach is no longer relevant in modern cloud data warehouses. Modern tools like dbt make it easy to create fact and dimension tables, which can then be easily converted into Wide Tables or Activity Schemas as needed, providing a flexible and easy-to-use solution for modern data modeling. The traditional Kimball approach has its advantages, such as providing a blueprint and being a common standard, but also has limitations, including the need for joins that can make it hard to navigate for business users.

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