What is data lineage and why is it relevant to CDI metrics?

• A. Data storage location.
• B. Data origin and transformations; important for trust, audits, and regulatory compliance.
• C. Data encryption.
• D. Data visualization.

Answer: (B)

Data lineage is the record of where data comes from, how it moves through systems, and every transformation it undergoes from source to the final metric. In CDI metrics, understanding this path is crucial because those metrics are built from data that often flow through multiple sources, ETL steps, and calculations. Knowing the lineage lets you trace a metric back to its origin, verify that the right fields and rules were used, and see exactly what transformations were applied along the way.

This visibility supports trust and audits, since you can demonstrate how a metric was produced and why it’s valid. It also aids regulatory compliance by showing data provenance and change history, and it enables reproducibility and impact analysis—if a source or rule changes, you can quickly assess how the CDI metrics will be affected. Data lineage thus underpins governance, quality, and accountability for metrics.

The other options miss the point: storage location is merely where data resides, not how it was produced; encryption is about securing data rather than tracing its origins and transformations; visualization is about presenting data, not the lineage and provenance of the data used to compute metrics.