When Column Names Lie: Bringing External Catalogs to NL2SQL++

Natural Language to SQL++ (NL2SQL++) relies heavily on schema knowledge, which is often problematic due to opaque or misleading column names typically found in enterprise data. This project addresses these challenges by connecting enterprise data catalogs to Couchbase, allowing NL2SQL++ to access accurate column metadata, including descriptions and relationships, rather than relying solely on column names. The system integrates a pluggable provider pattern to accommodate various catalogs and utilizes vector search to embed and retrieve relevant metadata at query time, ensuring schema information is not hardcoded. This enables accurate query generation, even when schemas change, by leveraging metadata from catalogs like DataHub and OpenMetadata. The approach enhances the accuracy of SQL++ generation, especially in cases where column names are ambiguous or misleading, by ensuring that the correct columns and join relationships are used to produce the desired results. This method not only improves query accuracy but also allows organizations to seamlessly integrate their existing catalogs into AI-driven query generation, offering a flexible and scalable solution for schema-aware data querying.

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