Which data governance component helps track the origin and transformation of data as it flows through AI workflows?

Which data governance component helps track the origin and transformation of data as it flows through AI workflows?

• A. Data lineage
• B. Access controls
• C. Data encryption
• D. Data retention policy

Answer: (A)

Data lineage records the origin of data and every transformation it undergoes as it moves through AI workflows. This means you can trace a data item from its source, through preprocessing, feature engineering, and data merges, all the way to the model inputs and outputs. That end-to-end visibility is essential for reproducibility, debugging data quality issues, and assessing how changes to data affect model behavior. In governance terms, lineage provides provenance and accountability across the data life cycle, which is crucial when models rely on complex or evolving data sources. The other options serve different purposes: access controls limit who can view or modify data; encryption protects data confidentiality; and a data retention policy dictates how long data is kept, not how it originates or is transformed through workflows.

Data lineage records the origin of data and every transformation it undergoes as it moves through AI workflows. This means you can trace a data item from its source, through preprocessing, feature engineering, and data merges, all the way to the model inputs and outputs. That end-to-end visibility is essential for reproducibility, debugging data quality issues, and assessing how changes to data affect model behavior. In governance terms, lineage provides provenance and accountability across the data life cycle, which is crucial when models rely on complex or evolving data sources.

The other options serve different purposes: access controls limit who can view or modify data; encryption protects data confidentiality; and a data retention policy dictates how long data is kept, not how it originates or is transformed through workflows.