What is SETSQL?
SETSQL is a research and development project aimed at bridging the gap between natural language and relational databases, enabling data querying and analysis without the need for complex SQL coding.
Objective and
technological background
The primary goal of the SETSQL project is to develop a Natural Language-to-SQL system that enables a more natural, reliable, and flexible interaction with databases.
The solution leverages cutting-edge Artificial Intelligence, including Machine Learning (ML), Natural Language Processing (NLP), and Large Language Models (LLMs), to interpret user intent and generate precise SQL queries.
Operation & Key Features
The operation of SETSQL is based on a sequential process of analyzing and transforming natural language queries::
The user formulates a natural language query, which the system interprets for meaning and structure, before generating the corresponding SQL query to retrieve the data.
At the same time, SETSQL integrates continuous learning loops, allowing the system to steadily enhance its accuracy and reliability through use.
Applications and Outlook
The project’s vision is to simplify and broaden data access by establishing natural language as the primary interface for information systems. This contributes to the creation of more accessible and efficient digital solutions.
Technology & Research
SETSQL is based on modern research approaches in the fields of Artificial Intelligence and Natural Language Processing, aiming to enhance the accuracy, performance, and reliability of the generated queries.
Natural Language Processing (NLP
- Semantic analysis of natural language queries
- Understanding user intent and context
- Adaptation to the linguistic peculiarities of the Greek language
- Analysis of complex and ambiguous formulations
Machine
Learning
- Model training for SQL query generation
- Optimization of results through feedback loops
- Support for continuous learning mechanisms
- Adaptation to new data schemas
Database Connectivity
- Support for relational databases
- Analysis of schemas and metadata
- Flexibility to adapt to different environments
- Generalized interface approach
Performance & Reliability
- Optimization of generated queries
- Reduction of execution errors
- System stability and scalability
- Data protection and access control
