Maybe I haven't found the right tool yet, but every time I see a product trying to solve data analysis with AI, the first example often deals with aggregated revenue over time or something similar.

This can be solved by a student after 3 days of learning SQL from scratch.

The article, while technical, remains pretty vague about implementation and what real, business problem they managed to solve with such a framework.

Of course building on top of a semantic layer is good for LLMs, but that assumes 1. this semantic layer exists 2. it is not a freaking mess. While tools like dbt helped with 1, I'm yet to see a clean, well-documented, lineage-perfect semantic layer.

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djoldman 5 days ago | parent [-]

Agreed.

Data curation is barely on the radar of most non-tech industries. Even in tech, it's rare to have any meta data.

This is a huge blocker to many efforts.

Someone somewhere has to go through every table and field and document where it came from, when, and what it actually means.

Very very few places do this.

"Oh yeah I go to gold.inventory. I think it updates every night. Columns? Should be pretty intuitive, just look at the names."

	▲	mrklol 4 days ago \| parent [-]
		But IF there’s documentation a LLM could help and find things faster than a "new“ human who isn’t familiar with all the tables. I would rather see it as a helper - maybe even more with good architecture and docs.