Machine learning data catalogs (MLDCs) are more than a metadata management tool and marketplace. Standalone tools provide an enterprise hub across the ecosystem and solution- and platform-based catalog and metadata repositories. This hub combines a traditional data management business glossary, data stewardship, data preparation, and data marketplaces for a central platform to serve contextualized data. Machine learning (ML) is the glue that makes this happen. ML automates the mundane aspects of understanding the data and applying policies, business rules, tags, and classifications. It provides introspection and inferencing to identify and anticipate error and conflict impacts. And it speeds up collaboration, data curation, and remediation with embedded intelligence and behavioral learning from a social media user experience (UX).
Collaboration, Lineage, And Data Variety Are Key Differentiators
Alation, Collibra, Alex Solutions, And IBM Lead The Pack; data.world, Informatica, Io-Tahoe, and Hitachi Vantara are Strong Performers in "The Forrester Wave™: Machine Learning Data Catalogs, Q4 2020"
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