AI POWERED NATURAL LANGUAGE TO SQL QUERY SYSTEM FOR CSV DATA ANALYSIS

The rapid growth of data across various domains has increased the need for efficient and user-friendly data analysis tools. However, extracting meaningful insights from structured datasets often requires knowledge of Structured Query Language (SQL), making data analysis difficult for non-technical users. To address this challenge, this project titled "Smart Data Analyzer" presents an intelligent web-based application that enables users to analyze CSV datasets using natural language queries without requiring SQL expertise.The proposed system allows users to upload CSV files, which are validated and stored in a SQLite database. The application utilizes Google's Gemini Large Language Model (LLM) to convert user questions written in plain English into valid SQL queries. To ensure database security, a SQL validation module permits only read-only SELECT queries while blocking potentially harmful operations such as INSERT, UPDATE, DELETE and DROP. The validated queries are executed on the SQLite database, and the results are displayed in tabular format.To enhance data interpretation, the system automatically recommends and generates interactive visualizations using Plotly based on the query results. Users can also export the generated results in CSV and Excel formats for further analysis and reporting. The application is developed using Python and Streamlit, providing an intuitive and responsive web interface for seamless user interaction.This project demonstrates the effective integration of Artificial Intelligence, Natural Language Processing (NLP), Database Management, and Data Visualization techniques to simplify data analysis. By eliminating the need for manual SQL coding, the proposed system improves accessibility, enhances productivity, reduces analysis time, and empowers both technical and non-technical users to derive meaningful insights from structured data efficiently.