Conversational Data Analytics with SQL Embeddings
Your warehouse already contains an implicit "analytics brain" in the form of years of SQL; SQL embeddings make that brain searchable and reusable.
Embedding SQL + query metadata enables natural-language questions to map onto previously validated query patterns instead of generating SQL from scratch.
The most effective setups separate retrieval (find similar queries) from generation (adapt/combine them) and always pass domain + metric hints.
This shifts analytics from dashboard-hunting to decision flows backed by a shared SQL memory, without replacing your existing BI or warehouse.
https://hackernoon.com/conversational-da...source=rss
Your warehouse already contains an implicit "analytics brain" in the form of years of SQL; SQL embeddings make that brain searchable and reusable.
Embedding SQL + query metadata enables natural-language questions to map onto previously validated query patterns instead of generating SQL from scratch.
The most effective setups separate retrieval (find similar queries) from generation (adapt/combine them) and always pass domain + metric hints.
This shifts analytics from dashboard-hunting to decision flows backed by a shared SQL memory, without replacing your existing BI or warehouse.
https://hackernoon.com/conversational-da...source=rss
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