datam

Datam is a concept in information technology referring to a data-centric model for organizing, governing, and discovering data assets through explicit management of metadata and provenance. The term is a portmanteau of data and metadata, and is used in some data governance and data cataloging discussions to emphasize metadata-first approaches.

In practice, datam describes an architecture in which datasets, their schemas, lineage, quality metrics, access policies, and transformation history are first-class citizens. Core components include DataAsset objects (datasets, tables, files), MetadataRecords (descriptive, technical, and operational metadata), lineage graphs showing data movement, and governance policies.

Applications include data cataloging, impact analysis, regulatory compliance, data stewardship, and data quality monitoring. By making metadata and provenance explicit, datam-oriented systems aim to improve data discoverability, trust, interoperability, and auditable governance.

Standards such as Dublin Core, DCAT, and W3C PROV are commonly used to facilitate interoperability, while many implementations map their datam models to relational, graph, or data-lake architectures.

History and usage: Datam arose in industry and academic discussions as a conceptual emphasis on metadata-centric data governance. It is not a formal standard or universally adopted term; implementations vary between organizations and platforms.

Criticism: The concept can add complexity and maintenance overhead, and its benefits depend on disciplined metadata capture and consistent governance practices.