What is a best practice for managing data lineage in an organization?

• A. Track every data asset exhaustively.
• B. Restrict the scope to the most important applications and work backward in the context of a business value stream.
• C. Ignore lineage and focus on privacy.
• D. Only lineage data related to customer records.

Answer: (B)

Understanding data lineage means tracing how data originates, how it moves, and how it’s transformed so governance, risk, and quality controls can be applied. The best practice is to scope lineage around the most important business value streams and work backward to identify the data assets and transformations that realmente affect those processes. This risk‑driven, value‑focused approach keeps governance practical, scalable, and aligned with real decision‑making, while still enabling effective change impact analysis and privacy protections.

Tracking every data asset exhaustively tends to create noise and heavy maintenance burden, making lineage unwieldy and less actionable. Focusing only on customer records is too narrow and would miss other crucial data flows that influence operations, finance, or analytics. Ignoring lineage altogether eliminates the ability to assess impacts of changes, meet regulatory needs, and understand data dependencies.