When data modelling is worth the effort

Most teams know this matters. Fewer have decided who owns it. Data modelling is not free, and pretending otherwise leads to bad decisions.

Numbers get quoted in meetings long after anyone remembers how they were calculated. Doing this properly once is usually cheaper than doing it approximately three times.

When it is worth it

The model outlives the application built on top of it. There is a version of this that is over-engineered, and it is worth avoiding. Most teams find the first pass takes an afternoon and the maintenance takes minutes a month.

When it is not

If nothing downstream depends on it and nobody is complaining, it can wait. That sounds obvious written down. It is still the thing most often skipped.

How to decide

Model what is true, not what is convenient this quarter. The teams that handle this well are rarely the ones with the biggest budgets. Anything you cannot measure here, you are deciding by taste, which is fine as long as everyone knows it.

In practice

Data outlives the applications built on top of it, which is why the model deserves more thought than the screens. 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

If any of that sounds like a description of your current setup, it is fixable.