PREreview del Text-to-SQL for Enterprise Data Analytics

Summary

The paper explains how LinkedIn developers created an enterprise Text-to-SQL system which enables users to perform self-service analytics on their expanding data lake. The system unites three components which include a knowledge graph and Text-to-SQL agent and interactive chatbot to perform data discovery and query generation and debugging functions.

Contribution

The research presents an operational complete system design for business Text-to-SQL operations which achieves results that exceed traditional benchmark results. The research delivers specific methods which unite knowledge graphs with query logs and interactive agent development to create Text-to-SQL systems which work effectively in actual business environments.

Relevance

The research provides vital findings because organizations encounter difficulties when they attempt to deploy Text-to-SQL systems with their present big language models. The enterprise focus together with real usage metrics in this contribution make it especially valuable.

Approach

The methodology is appropriate and well motivated. The knowledge graph enables Text-to-SQL systems to solve their main failure points which include schema ambiguity and hallucinations through its combination of metadata and historical queries and domain knowledge.

Strengths

Real-world deployment at enterprise scale

The presentation shows how operational challenges affect system performance through its demonstration of both system operational problems and system operational trade-offs.

The research performs ablation studies to identify which components generate the most important results.

The system needs to focus on creating an easy-to-use interface which users can operate effectively instead of making search accuracy its main priority.

Limitations

The reported accuracy demonstrates major progress but it reveals multiple reliability problems which need to be solved. The results use an internal benchmark system which makes it difficult to compare with outside organizations.

Overall assessment

The research presents a robust method which enables Text-to-SQL system deployment for enterprise analytics environments.

Competing interests

The author declares that they have no competing interests.

Use of Artificial Intelligence (AI)

The author declares that they did not use generative AI to come up with new ideas for their review.