World Congress 2026 Europe - Virtual Stage • Jul 2, 2026 • Session details

Beyond Dashboards: Fixing Text-to-SQL with Semantic RAG

Piotr Menclewicz

Why do language models hallucinate enterprise SQL? Learn how Semantic RAG uses your semantic layer as a blueprint to safely write custom queries for unpredictable business questions.

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#1 about 2 min

Why language models struggle with enterprise data queries

Throwing raw database schemas at probabilistic language models causes hallucinations because they lack critical business context.

#2 about 2 min

Moving the semantic layer upstream to avoid vendor lock-in

Shifting semantic logic out of dashboarding tools creates a universal headless layer that standardizes metrics across downstream applications.

#3 about 2 min

Categorizing business queries to expose semantic layer limitations

Predefined semantic models successfully handle routine metric breakdowns but fail during complex, ad-hoc investigations that require deep data exploration.

#4 about 2 min

Implementing semantic RAG with fallback for complex queries

Treating the semantic layer as a blueprint for generating custom SQL enables artificial intelligence agents to accurately answer unexpected questions.

#5 about 1 min

Preparing enterprise data foundations for artificial intelligence agents

Building reliable artificial intelligence solutions requires data teams to proactively document and expose underlying semantic context before deployment.

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