AI-Powered SQL Assistant: Transforming Natural Language into Optimized SQL Queries
Authors:-Atharv Deshmukh, Manali Gawade, Ronit Fulari
Abstract-Databases have a steep learning curve, littered with schema design, SQL di- alects, and performance optimizations. Formulating efficient SQL queries is a chal- lenging process to tinker with, and this is one of the reasons many developers and analysts are blocked. Here we present an AI-based SQL Assistant that utilizes cutting-edge AI models to transform natural language requests into fast SQL code. It lives on top of a variety of SQL dialects, including Spark SQL, PostgreSQL, and MySQL, and provides schema suggestions and smart executor queries. It can use a feedback loop with machine learning methods to improve performance after the sys- tem is deployed based on users adapting the system to query patterns. We provide experimental evidence to show that the proposed solution not only improves query performance and execution time but also accuracy so that the database interactions are smooth for non-experts.
