A training dataset changes silently between experiment runs, making comparisons unreliable. Which approach best fits?

1. Version or snapshot the training data and record its lineage.
2. Establish shared documented feature definitions and validated transformations.
3. Use controlled managed development environments and least-privilege identities.
4. Track experiment metadata and versioned artifacts.