Explain data lineage and its importance in MDC3?

Explain data lineage and its importance in MDC3?

• A. Data lineage traces data from source to destination through transformations; supports governance, impact analysis, and auditability in MDC3.
• B. Data lineage is about lineage of teams.
• C. It's not relevant to governance.
• D. It only tracks data age.

Answer: (A)

Data lineage traces data from its source to its final destination, showing every transformation and move it undergoes and the dependencies it creates. In MDC3, this understanding is crucial for governance because it provides provenance—so you can verify where a value came from and how it was produced. It also enables impact analysis: when a source, rule, or transform changes, lineage reveals all downstream assets—reports, dashboards, datasets, or models—that are affected. And it supports auditability, since you can trace data flows step by step during audits or regulatory reviews. This clarity goes beyond simply knowing data age or team structures; data lineage is about the data’s journey and its transformations across the system.

Data lineage traces data from its source to its final destination, showing every transformation and move it undergoes and the dependencies it creates. In MDC3, this understanding is crucial for governance because it provides provenance—so you can verify where a value came from and how it was produced. It also enables impact analysis: when a source, rule, or transform changes, lineage reveals all downstream assets—reports, dashboards, datasets, or models—that are affected. And it supports auditability, since you can trace data flows step by step during audits or regulatory reviews. This clarity goes beyond simply knowing data age or team structures; data lineage is about the data’s journey and its transformations across the system.