Talk2DB – AI-Powered Natural Language Data Base Assistance
DOI:
https://doi.org/10.47392/IRJAEH.2025.0265Keywords:
Streamlit application, SQL automation, Natural language processing, Database interaction, Data visualizationAbstract
In today’s data-driven environment, non-technical users often struggle to access and analyze data stored in relational databases due to a lack of knowledge in SQL. This research presents Talk2DB, a user-friendly web application designed to bridge this gap by allowing users to interact with a MySQL database using natural English queries. The goal is to empower store owners and managers with simple data retrieval and visualization tools without requiring technical expertise. The application uses Streamlit for the frontend and integrates Gemini for natural language processing and SQL query generation. The backend is secured with SQLAlchemy and bcrypt for user authentication. Core features include English-to-SQL conversion, SQL-to-Excel data downloads, file uploads with previews, automated visualizations with textual insights, and a centralized dashboard for interactive data exploration. System evaluation demonstrated that Talk2DB effectively lowers the technical barrier for data access, enhancing usability and supporting better decision-making for non-technical users. Tests conducted on a sample retail database showed users retrieving valuable insights quickly using plain English queries. The successful implementation of Talk2DB highlights its potential as a practical solution for real-time business analytics, especially suited for small to medium-sized enterprises. It simplifies the data interaction process and provides meaningful insights without the need for SQL knowledge, making data analysis more inclusive and efficient.
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