Data modelling: the questions we get asked most

We end up explaining this on discovery calls often enough that it deserved writing down. The questions about data modelling that come up most often on our calls.

Data outlives the applications built on top of it, which is why the model deserves more thought than the screens. The failure mode is not doing it wrong, it is doing it once and assuming it stays done.

Do we need to care about this?

The model outlives the application built on top of it. It is worth being explicit about, because assumptions differ quietly. The failure mode is not doing it wrong, it is doing it once and assuming it stays done.

Can it wait until after launch?

Occasionally. More often the post-launch version costs several times the pre-launch one. Small and consistent beats large and occasional here.

How do we know it is working?

Model what is true, not what is convenient this quarter. That sounds obvious written down. It is still the thing most often skipped. It rarely shows up as a line item, which is exactly why it slips.

How to tell if yours is fine

Most data problems are ownership problems that turned into technical ones. Three things worth confirming about data modelling before you move on:

• Someone can say what the current setup is without going to look
• Model what is true, not what is convenient this quarter — and you know whether that is true here
• There is a way to tell whether the last change to this helped

Pick the one that would hurt most if it failed, and start there.