Dataset Versioning Governance overview

Governs the versioning lifecycle of ML training and evaluation datasets — enforcing DVC or LakeFS versioning policies, validating that dataset lineage metadata tracks transformations and source provenance, auditing storage deduplication, managing access controls per dataset sensitivity tier, and ensuring reproducibility by linking model artifacts to exact dataset versions. Excludes dataset creation and labeling.