Towards Agentic Schema Refinement

2024-11-25 · Agapi Rissaki, Ilias Fountalis, Nikolaos Vasiloglou, Wolfgang Gatterbauer

Large enterprise databases can be complex and messy, obscuring the data semantics needed for analytical tasks. We propose a semantic layer in-between the database and the user as a set of small and easy-to-interpret database views, effectively acting as a refined version of the schema. To discover these views, we introduce a multi-agent Large Language Model (LLM) simulation where LLM agents collaborate to iteratively define and refine views with minimal input. Our approach paves the way for LLM-powered exploration of unwieldy databases.

📄 PDF Abstract BibTeX arXiv:2412.07786

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Language ModelingLanguage ModellingLarge Language Model

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