Enhanced Text to SQL Parser

Abstract

Text-to-SQL parsing is an important research area in natural language processing that enables users to interact with databases using plain English queries. Traditional database systems require knowledge of structured query language (SQL), which limits accessibility for non-technical users. This paper proposes an Enhanced Text to SQL Parser that converts natural language questions into accurate and optimized SQL queries. The system integrates Natural Language Processing (NLP), semantic analysis, and schema understanding to generate reliable SQL statements. The proposed solution improves query accuracy, reduces human effort, and enables intelligent database interaction for academic, business, and enterprise applications.