datadatabaser

Datadatabaser is a term used to describe a person, organization, or software component that creates, maintains, and uses datadabases—repositories that describe other data. Datadabases focus on metadata, data dictionaries, data catalogs, and lineage information, rather than the primary data content itself. The term highlights the role of metadata as a first‑class citizen in data ecosystems.

In practice, datadatabasers define metadata schemas, catalog datasets, record data provenance and quality metrics, and implement discovery and governance features. They work within data platforms, information architecture teams, or dedicated metadata management programs. The work typically spans data modeling, schema evolution, access control, and documentation to improve data discoverability and reuse.

Datadatabasers can be human professionals such as data engineers or data stewards, or software systems such as metadata management tools. They often rely on standards and interoperable stacks, including DCAT for catalog data, PROV for provenance, and integrations with data catalogs like Apache Atlas, Amundsen, or DataHub. Effective datadatabasing enables data lineage, impact analysis, data quality tracking, and policy enforcement across data pipelines.

Common challenges include maintaining up‑to‑date metadata across heterogeneous sources, aligning schemas with changing datasets, ensuring trust and provenance, and balancing openness with security and compliance.

See also: metadata, data governance, data catalog, data lineage, data stewardship.