Welcome to IGNITE GenAI
Case Studies
Crafting a Comprehensive Data Dictionary for a Massive Database System with Generative AI in a few Weeks
CXOs, Data Engineering Teams
Problem Statement
- A leading retail company had a vast database system, but without a clear data dictionary, understanding and utilizing the data became a challenge.
- The sheer volume of tables and the lack of documentation meant that developers and analysts spent excessive time trying to decipher data structures.
- Manual efforts to create a data dictionary were deemed time-consuming and prone to errors, given the database's complexity.
Solution
Harnessing the power of Generative AI, our team embarked on a mission to automate the creation of a comprehensive data dictionary
- We built a tool that would deep dive into the database, extracting table definitions and sampling data from each table.
- Using proprietary techniques and Generative AI analyzed the extracted information, identifying patterns, relationships, and data types.
- The tool generated a comprehensive draft dictionary with detailed descriptions for each table, column, and relationship, ensuring clarity and accuracy.
- The tool also had capabilities to identify and recommend critical data elements including PII, PCI and other custom compliant requirements.
- The SMEs and data owners were able to quickly validate and finalize the data dictionary with ease.
- The Critical Data Element identifier was a key differentiator that immensely empowered data owners, architects and developers for supporting data management, governance and reporting.
Benefits
- What would have taken months of manual effort was accomplished in a few weeks, freeing up valuable resources.
- The AI-driven approach ensured that the data dictionary was precise, with minimal errors.
- Developers and analysts could now quickly understand the database structure, speeding up development and analysis tasks.
- This solution transformed a daunting task into a streamlined process, delivering a comprehensive data dictionary that empowered the team to work more efficiently.
Conclusion
Our custom solution was designed to handle multiple projects simultaneously, catering to the growing demands of the business. It accelerated data dictionary creation for over 3800+ tables and datasets residing in a variety of data platforms with minimal documentation and no SME support. Over 91000+ attributes were processed and tagged with descriptions, sample domain values.
