Active metadata management is a new form of data management where active metadata is used to provide clear, intelligible business insights to drive smart business decisions. Active metadata is the key factor that will allow businesses to improve the efficiency of data-driven decisions and initiatives. Metadata is data that describes data. Traditional data catalogs contain passive metadata—data not proactively used by the user unless initiated and includes models and schemas. This is where active metadata comes in. Active metadata enriches passive metadata to improve data cataloging and data management. It manages the metadata for operational purposes.
Traditional metadata management platforms focused on organizing and storing metadata, including an organization's data. Active metadata management brings in the "analysis" component to this data, helping data users analyze metadata and derive valuable and rational insights via automation. In simple terms, metadata management connects technical, business, and operational data, and when AI and machine learning are integrated into this relationship, active metadata management is born. Active metadata management platforms also have a component of machine learning to ensure resource allocation, capacity monitoring, etc. It also supports real-time collaboration.
Active metadata management software works very similarly to machine learning data catalogs. The major difference, however, is that active metadata management encompasses the entire data ecosystem and is the successor to a machine learning data catalog. Active metadata management tools do not focus only on crawling, cataloging, and scrolling data with the help of machine learning but also set up a data management framework for all users in an organization. It is a building block of the DataOps architecture.
To qualify for inclusion in the Active Metadata Management category, a product must:
- Manage a company’s active metadata and provide intelligent, actionable insights
- Build a knowledge graph of metadata management
- Support integration with API connectors for collaboration
- Enable personalization of recommendations for data analysis and adjacent management tools
