This research, by Dr Ashu Abdul, Assistant Professor and research scholar Ms Surya Samantha Beri along with forth-year student, Mr Jakkampudi Venkatasubbaiah from the Department of Computer Science and Engineering explores a framework designed to help users retrieve and analyse data without requiring any Structured Query Language (SQL) knowledge. The patent titled, “Empowering Data Access: A Framework for SQL-Free Database Interaction, with application no: 202441096460 is particularly relevant as it enables individuals, like a car dealer seeking sales insights, to interact with their databases using everyday language. Such accessibility underscores the importance of this research in democratising data access for all users.
Abstract:
This project is centred around creating a framework that translates user queries into SQL statements and retrieves results without requiring any SQL knowledge from the user. By delving into the workings of various RDBMS systems, with a special focus on MySQL, I developed a solid understanding of database architecture and how databases are engineered for optimized performance. This knowledge was critical in designing a system that can seamlessly interact with any given database, analyse it, and provide relevant results in response to user input.
About the Framework:
This framework is intended to convert the user queries into SQL statements and attain the results from the database without intervention of SQL coding. Every time writing multiple SQL commands to apply filters, commands, and extracting data is time-consuming and requires having knowledge of SQL knowledge. This project is intended to analyze a database and answer the questions that are related to a particular database without writing SQL commands.
Explanation in Layperson’s Terms:
In-General we rely on programmers who are efficient in programming SQL for finding the insights from the database which are related to business or information. So, Laymen cannot access data without knowing SQL this project makes it possible. Assume, Mr. A a car dealer owns a showroom has a software dealing with his Business he wants to access his data and get insights for understanding the sales. Now he is not familiar with using SQL so he relies on someone for that or opens software and applies multiple filters to analyze his data. But What if he can use a chatbot and get solutions for all his questions from his database?
Mr.A can get conclusions from his data within no-time that thought represents this entire project.
What are the use cases of this framework to a layman?
Laymen interaction with the database for understanding their data. Reducing the requirement to understand and search for the filters in the front-end. Faster data extraction from the database. Generating the results based on user queries in natural language without SQL coding. Elimination of time and efforts required for writing SQL Commands or applying filters. Understanding data gets easier for engineers as well as unknown data can be understood easily.
Practical Implementation:
This project has been successfully integrated into several existing real-time applications, enabling precise identification of data locations. By fine-tuning and enhancing our algorithms, we have achieved significant improvements in accuracy. In practical terms, users can effortlessly explore and comprehend their data.
Furthermore, extensive testing across databases of varying sizes has demonstrated the project’s ability to deliver significant and well-structured results.
Future Enhancements:
Incorporating Natural Language Processing (NLP) to process and respond to queries in users’ native languages, including speech-to-text capabilities.
Facilitating the generation of dynamic reports in various formats such as PDFs and Excel sheets.
Expanding compatibility to support additional database systems like Oracle, PostgreSQL, and NoSQL models.
Enabling data extraction and analysis from Excel sheets and CSV files.