Introduction

Welcome to the Dimensional Modelling Docs — a shared, practical source of truth for building dimensional (Kimball-style) data warehouses and marts. It collects the concepts, definitions, and reference models we rely on when designing facts and dimensions, written to be useful both to the analytics engineers on the team and to the LLMs that assist them.

Why this guide

There are many excellent Kimball books and tutorials, but we kept hitting the same gaps. They were:

• Not written for LLMs — hard to feed to an assistant as ground truth.
• Light on concrete examples — strong on theory, thin on the exact SQL and edge cases you actually meet in production.

So this guide is deliberately pragmatic: short explanations backed by real examples we have encountered while developing facts and dimensions in production.

Concepts

The Concepts section covers the foundational building blocks of dimensional modelling — the ideas you compose into a model. Start with the Dimension, see how dimensions and facts fit together in a Star Schema, then learn how rows are identified and linked in Kimball Keys Definitions.

Definitions

The Kimball Group website already offers excellent, concise definitions. Here the focus is narrower: collect the terms that come up most often during development, each as a short, self-contained definition with an example where it helps. See Degenerate Dimension or Slowly Changing Dimension for the shape these take.

Reference

The Reference section is a growing catalogue of the facts and dimensions you meet in real-life scenarios. Each page documents one entity — its grain, schema, worked SQL, and common pitfalls — so you have a standard to design and build from (and one an LLM can quote). Standard Cost is the first worked example.