Course note — Rows, grain, and the shape of a dataset

Revised Rows, grain, and the shape of a dataset this week. The change was small and the reason was not.

Nearly every wrong number in a career traces back to someone not knowing what one row of their table represents.

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 Foundations 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 What a data team is actually for and leads into Turning a request into a question, 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.