Data Quality Driven By Generative AI
Source: Juan Ramón González
Creating and deploying quality rules simply, error-free, and using natural language is now a reality with OMMA!
Through the integration of Large Language Models (LLMs), we have transformed this process, making it more accessible, efficient, and accurate. This evolution of our OMMA tool allows users to formulate quality rules in natural language, thus facilitating data management without the need for advanced technical knowledge.
With this development, we have evolved our solution to achieve:
- Process Simplification: OMMA allows users to define data quality policies using natural language. This capability reduces the complexity of the process, making it more intuitive and accessible.
- Enhanced Efficiency: Creating data quality rules is now faster and less error-prone, accelerating implementation and improving accuracy.
- Comprehensive Transformation: The ability to generate multiple rules from a single instruction and convert SQL statements into usable rules represents a significant advancement in data quality management.
At the architectural level in OMMA and LLMs, we have made significant advancements, such as:
- Intelligent Agent Architecture: We have developed an agent structure that coordinates all the actions necessary for rule creation in OMMA. We use GPT-4O and GPT-3.5 turbo models to handle specific tasks, ensuring precision and consistency.
- Modularity and Scalability: The modular architecture facilitates system extension and maintenance, allowing for new functions to be added and adapting to changing requirements easily.
- Defined Execution Flow: A central planner coordinates the execution flow, ensuring that each step is carried out in a structured and reliable manner.
- End-to-End Integration: From rule generation to review on the front end, OMMA provides a robust and seamless user experience, integrating generative AI at every stage of the process.
And this is not the end. We continue to evolve OMMA continuously to improve its functionality, usability, and outcomes. Therefore, we are currently working on new integrations, such as an intelligent rule recommender and the ability to convert SQL statements into usable rules, to further optimise data quality management.
Additionally, we are exploring the implementation of LangGraph to further enhance our agent architecture.
OMMA has evolved to redefine data quality management. With technologies such as Generative AI, OMMA offers an accessible, efficient, and accurate solution that adapts to the needs of any organisation, improving their results and competitive advantage.
Find out how we made it possible.
Read the full article HERE and revolutionise data quality in your sector with OMMA.
