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You have to go back a step, to ETL vs ELT. ELT is powerful because you're doing the transformations as the final step, so you can quickly ingest the data and th
by panda888888 4y ago
You have to go back a step, to ETL vs ELT. ELT is powerful because you're doing the transformations as the final step, so you can quickly ingest the data and then transform it however you want and in different ways. While you may not love DBT, the innovative thing here is that the IT department no longer needs to do this work (this is in contrast to ETL). A data analyst or business analyst or anyone who knows SQL can now do it. So if you're a software engineer, you're probably not the target audience for DBT. I agree with your criticism that the tool itself isn't necessarily that innovative, but if you think of DBT as version control/templating for people who aren't already software engineers, it's easier to see why it's useful.
- FridgeSeal 4y ago> You have to go back a step, to ETL vs ELT. ELT is powerful because you're doing the transformations as the final step, so you can quickly ingest the data and then transform it however you want and in different ways No I get it, land your data, apply transforms land it, repeat. I’m already following this approach, so maybe the value prop of dbt is lost on me. My concern is that I’ve worked in places where the proverbial “reigns” of “do whatever” with the data were handed off to anyone who asked for them, and I was involved trying to fix the inevitable mess that was created. There’s zero coherency, so 8 different people create 5 different, incompatible reports for the same thing, mishandled money and date values everywhere, etc. That’s not an experience I wish to relive any time soon.
- panda888888 4y agoThat sounds like a data governance problem that goes above and beyond the things that DBT does. The typical way to handle this is by implementing a gold/silver/bronze architecture.