How to get data modelling right
The gap between knowing this and actually doing it is where most teams lose ground. The short answer to data modelling is that it is mostly a sequence of small decisions, not one big one.
Most data problems are ownership problems that turned into technical ones. The teams that stay on top of it are the ones who put it on a calendar rather than a wish list.
Why this earns attention
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 two people in the business would answer this differently, that gap is the actual problem.
The steps
- Establish what you have today before changing anything
- Name things the way the business names them
- Model what is true, not what is convenient this quarter
- Write down the decision so the next person does not re-litigate it
Model what is true, not what is convenient this quarter. None of that requires a large budget, only a decision and someone to own it. The practical test is whether someone new to the project could tell, in a minute, that it had been handled.
Where to go from here
What this looks like day to day
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
- Name things the way the business names them — 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.