A Smart SQL Agent: Enhancing Big Query Efficiency and Usability
Abstract: This paper presents a comprehensive methodology for developing a SQL agent leveraging LangChain to interact with Big Query. The agent facilitates seamless generation and execution of efficient SQL queries against Big Query, returning results in a readily interpretable format. We explore optimization strategies for enhancing agent performance and delve into advanced functionalities including natural language processing (NLP) powered query construction and data visualization techniques. Best practices for integrating LangChain with Big Query are also discussed, providing developers with a practical guide to building robust and performant data access solutions.
Keywords: sqlagent, bigquery, langchain, sqlalchemy, sqloptimization
How to Cite?: Pushkar Vashishtha, "A Smart SQL Agent: Enhancing Big Query Efficiency and Usability", Volume 14 Issue 5, May 2025, International Journal of Science and Research (IJSR), Pages: 469-473, https://www.ijsr.net/getabstract.php?paperid=SR25423072212, DOI: https://dx.doi.org/10.21275/SR25423072212