Three myths about data modelling
There is no clever trick in this one, just a handful of decisions worth making deliberately. A few things about data modelling that get repeated more often than they get checked.
Numbers get quoted in meetings long after anyone remembers how they were calculated. It rarely shows up as a line item, which is exactly why it slips.
“It only matters for big sites”
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. If it only works because one person remembers to do something, it does not work yet.
“We can deal with it after launch”
Sometimes true, usually expensive. The teams that handle this well are rarely the ones with the biggest budgets.
“Our platform handles it”
Model what is true, not what is convenient this quarter. The teams that handle this well are rarely the ones with the biggest budgets. Write the reasoning down alongside the decision, because the reasoning is what changes first.
What this looks like day to day
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
Worth checking on your own setup before it becomes someone else's problem to fix.