Metadata management is another key pillar of EIM. Metadata is often defined as data about data and provides a context to the data it is associated with. Metadata can be managed through a set of defined processes wherein metadata is captured at each stage of a data management project. This ensures complete data lineage and traceability of data attributes as they move from information sourcing to information delivery and consumption. The common metadata types include the following:

§  Business metadata
Includes business requirements, business metrics, and key performance indicators, business terms, business process flows, and so forth.

§  Technical metadata
Captures details concerning data models; ETL job designs; and ETL mapping metadata, which provides detailed insights into the data processing job design and workflows.

§  Operational metadata
Captures details concerning operational metrics of running the ETL batch or reports batch. Statistics collected can be analyzed over time to monitor trends as well as look at data quality issues.