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Data and analytics

Data engineering in the model era: preparing data, analytics without SQL, and why text-to-SQL keeps breaking.

2 articles

A 31-subtype error taxonomy beats blind retries in text-to-SQL

Turning a human question into correct SQL is a surprisingly hard problem. Large language models write valid syntax well but miss the logic easily: they confuse tables, join on the wrong key, forget GROUP BY, apply the wrong filters. Plain self-correction from execution results doesn't always help — a query can run fine and even return something plausible that still isn't what the user asked…

IBM puts Granite time-series models inside Confluent's Flink SQL

IBM has moved its Granite time-series foundation models inside Confluent's stream processor. Four of them — PatchTST-FM, FlowState, TTM and TSPulse — are in early access on Confluent Cloud on AWS, callable from Flink SQL through two functions Confluent already ships, AI_FORECAST and AI_DETECT_ANOMALIES. Swapping one model for another is a single parameter change, with no pipeline to rebuild.…