Artificial Intelligence is significantly impacting data catalogs. Modern machine learning augmented Data Catalogs automate metadata discovery and profiling.
How can AI improve the way you find and trust your data?
ML Augmented Data Catalogs provide an AI-driven search and discovery of data assets including recommendations. The same way Google rank results when you type in data, augmented data catalogs browse through thousands of possibilities. They rank the result based on popularity, history, relationships, quality, etc.
Modern Data Catalogs establish a semantic relationship between data using knowledge graphs. They also provide data anomaly detection to identify sensitive PII information flagging risky data assets and outliers.
ML augmented Data Catalogs enable the pervasive use of metadata not just for Data Governance but also to automate data integration, data preparation, data quality, and many other data management activities. This next-generation Data Catalog can, therefore, accelerate time to insights by helping data teams automate most of the data discovery, tagging, propagation, and collaboration.
If you want to know more about plug-and-play, collaborative, ML oriented data catalogs: check Castor