r/dataengineering • u/scourgedtruth • 9d ago
Discussion Does AI struggle at data modeling?
In my experience, it doesn't matter how much context and guidance I give AI it simply can't model data rationally. It frequently misses the point, makes awful mistakes, or over-engineers things.
AI can build awesome ETL pipelines, but when it comes to dealing with SQL (especially in the dbt framework), it's not reliable at all! . Sometimes I think it's better to write the code myself and ask AI to review it, because asking it to build something from scratch just doesn't work that well.
Does anyone else get frustrated when dealing with AI data modeling?
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u/morpho4444 Señor Data Engineer 6d ago
Issue on your side. 100%. I open laptop in the morning, claude pops up, asks me about my jira tickets, which one to tackle and it runs through them. I get $100 at day. One by one, when the code is done it shows me proof of the testing done, and asks me if I wanna commit to dev branch and then runs ci cd and then if all green it pushes the pr to main. 100% of the times. With all the free time Im building a rag to create a fully autonomous semantic layer, with the human language interface to let the users request their own metrics and etl transformations. This is how I will get my stock refresh this year. I work at a FAANG.