Keydunov: Querying a semantic layer over raw SQL reduces LLM errors
Artem Keydunov · Powering your Copilot for Data - with Artem Keydunov from Cube.dev · Oct 27, 2023 · at 14:22
Artem Keydunov, co-founder of Cube, explains the technical workflow of using AI models to query enterprise data warehouses.
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“Now, the query, I believe, should be created against semantic layer, because it reduces the room for the error, because what usually happens is that your query to semantic layer would be very simple. It would be like, give me that metric grouped by that dimension, and maybe that filter should be applied. And then your real query for the warehouse, it might have like a five joins, a lot of different, you know, like a techniques, like how to avoid fan out, fan traps, chasm traps, all of that stuff. And the bigger query, the more room that the model can make an error, right? Like even sometimes it could be a small error, and then, you know, like your numbers is going to be off. But making a query against semantic layer, that sort of reduces the error.”
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