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A professional-level summary covering key definitions, frameworks, and exam-relevant points.
DMBOK Context
Data lineage is classified as a form of technical metadata in the DAMA DMBOK v2. It is managed within the Metadata Management knowledge area (11% CDMP weight) and is also relevant to Data Integration and Interoperability (6% weight). Lineage documentation is a core deliverable of any metadata management programme.
Lineage Types
| Type | Audience | Granularity | Focus |
|---|---|---|---|
| Technical Lineage | Data engineers, IT teams | Column-level, system-level | ETL jobs, transformations, database objects |
| Business Lineage | Analysts, stewards, compliance | Report-level, process-level | Business processes, KPIs, regulatory reports |
Use Cases
The primary use cases for data lineage are: impact analysis (understanding what will break if a source system changes), root cause analysis (tracing a data quality issue back to its source), regulatory compliance (demonstrating to regulators how personal data flows through the organisation), data trust (enabling consumers to verify the origin and transformation history of data), and migration planning (understanding dependencies before moving systems).
Lineage vs Provenance
The CDMP exam distinguishes between lineage (the movement and transformation history of data) and provenance (the origin, ownership, and authority under which data was created). Both are forms of technical metadata, but they answer different questions: lineage answers "where has this data been?"; provenance answers "where did this data come from and who is responsible for it?"