NATURAL LANGUAGE DATABASE QUERY AND ANALYTICS AGENT

Colleges record semester results in spreadsheets, and answering even a simple question about them, such as how one section performed compared with another, usually means filtering and calculating by hand or writing SQL. This paper presents the Natural Language Database Query and Analytics Agent, a system that lets non-technical users ask such questions in plain English. The agent supplies the schema of a relational database to a large language model, which writes a SQL query. The query is checked, executed in read-only mode, corrected using the database error message if it fails, and the result is returned as text, a table or a chart. The design is applied to the Information Science and Engineering result sheets of 206 students over three semesters (IV, V and VI). Example questions are run against the prepared database, and their answers are reported as ground truth for future testing, along with data-quality problems found in the source sheets. The measured accuracy of the model-generated queries is left for future work.