Analytics engineering: what to get right first

The gap between knowing this and actually doing it is where most teams lose ground. If you only fix one thing about analytics engineering this quarter, make it the first item below.

Data outlives the applications built on top of it, which is why the model deserves more thought than the screens. If it only works because one person remembers to do something, it does not work yet.

Start here

Transformations belong in version control like any other code. The teams that handle this well are rarely the ones with the biggest budgets. If it only works because one person remembers to do something, it does not work yet.

Then this

Tested, documented models stop every report disagreeing. Small and consistent beats large and occasional here. Budget a little time for it every quarter and it never becomes a project of its own.

Eventually

One definition of a metric, used everywhere. It is worth being explicit about, because assumptions differ quietly. The version that survives contact with a real deadline is the simple one.

How to tell if yours is fine

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

• Someone can say what the current setup is without going to look
• Tested, documented models stop every report disagreeing — and you know whether that is true here
• There is a way to tell whether the last change to this helped

The point is not perfection, it is knowing which of these you have consciously chosen to skip.