Enterprises run on data, but much of it sits in undocumented or poorly documented databases across multiple platforms. Creating data dictionaries manually is tedious, error-prone, and takes weeks of effort. Without proper documentation, analytics teams, compliance officers, and new employees struggle to understand what data means, how it should be used, and whether it meets governance standards. This slows down data initiatives, increases compliance risks, and makes enterprise data harder to discover and trust.
We built the Data Dictionary, an AI-powered platform that automates metadata documentation and profiling. It connects directly to multiple enterprise databases – SQL Server, MySQL, PostgreSQL, BigQuery, Redshift, Oracle, and Snowflake – extracts schemas, tables, and column-level details, and generates human-friendly documentation with AI-driven descriptions. The platform also profiles sample data to provide quality insights, and allows seamless export in multiple formats (Excel, PDF, Markdown, DOCX, JSON, Google Sheets).
The Data Dictionary is powered by a modern, AI-driven stack:
By turning undocumented systems into well-documented, AI-enhanced assets, the Data Dictionary accelerates cataloging, reduces compliance risks, and makes enterprise data accessible to everyone.
Ready to eliminate undocumented databases and accelerate compliance?
Partner with GenAI Protos to build AI-powered accelerators that turn your enterprise data into well-documented, trusted, and accessible assets.
Talk to GenAI Protos about Data Engineering Accelerators