Field note · May 8, 2024

Course note — Facts, dimensions, and picking a grain

Dimensional modelling is thirty years old and still the right default, because it optimises for the thing that actually matters — an analyst being able to answer a question without asking anyone.

1 min read ·Analytics engineering ·practice

Revised Facts, dimensions, and picking a grain this week. The change was small and the reason was not.

Dimensional modelling is thirty years old and still the right default, because it optimises for the thing that actually matters — an analyst being able to answer a question without asking anyone.

The first draft explained the mechanism and stopped. What was missing was the failure: the thing that happens when you get it wrong, described concretely enough that someone recognises it later. A lesson that only teaches the correct version leaves you unable to spot the incorrect one, which is the situation you will actually be in.

It sits in the Modelling the warehouse module, and the exercise runs against retail-orders. That pairing is deliberate: the dataset was built with the trap the lesson describes already in it, so the exercise fails in the instructive way rather than the confusing one.

Ordering matters here more than in most courses. It follows Schema drift, and the contract that prevents it and leads into Slowly changing dimensions, and the "as of when" problem, and reading it out of sequence mostly works but costs you the setup.

Free means free, and it also means we can rewrite it whenever it is wrong. No edition, no errata PDF, nothing to repurchase. The whole course is 36 lessons and the fixes land the day we find them.