Database Query and Reasoning
Gowtham Naidu Y · INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT · 2025
The rapid evolution of data-driven decision-making has highlighted the need for systems capable of seamlessly bridging the gap between natural human language and structured query languages like SQL. Traditional database systems often demand a technical understanding of SQL syntax and database schemas, creating significant barriers for non-technical users. To address this challenge, the "Database Query and Reasoning" project introduces an intelligent system designed to interpret natural language inputs, convert them into accurate SQL queries, and deliver both query results and explanatory reasoning for the outputs. This approach empowers users, regardless of technical expertise, to interact with complex databases effectively and derive actionable insights. Keywords: Natural Language Processing (NLP),AI Model Integration, CSV-to-Database Conversion, Reasoning Module,Query Result Visualization