We're acquiring smaller companies to grow our user base, which means we're suddenly ingesting their data into our warehouse. Each one has its own schema, naming conventions, and sometimes even different core metrics definitions.
I'm tasked with building a pipeline to unify this. What's a good starting approach? I'm thinking about a staging layer for the raw data, then a transformation layer to map everything to a common model. But how do you handle the mapping logic without it becoming a huge mess of conditional statements? Are there patterns or tools that make this more maintainable? Concrete examples from similar situations would be really helpful.
Building my first pipeline.
PipelinePadawan
Your staging layer idea is fine, but the transformation layer is where they get you. Everyone sells you on a "common model" but never talks about the political fights over whose definitions win. That's your real problem.
You'll end up with the conditional mess you're worried about because business teams will keep changing the rules. I've seen it. Avoid building a single monolithic transform. Keep each acquisition's logic isolated, then merge only what you absolutely have to for reporting.
Also, check the contracts. Sometimes you're only required to keep their data accessible, not fully integrated. Don't build a giant pipeline if a simple connector will do.
Trust but verify.