Dataset Versioning & Reproducibility (DVC)¶

Role of DVC¶

DVC provides:

• dataset versioning,
• data lineage,
• reproducible pipeline execution.

It acts as the bridge between data engineering and ML engineering.

Versioning semantics¶

Each dataset version is tied to:

• a specific snapshot in object storage,
• a git commit,
• downstream ML artifacts.

Reproducibility guarantee¶

Given:

• git commit hash,
• DVC version,
• configuration snapshot,

any experiment can be reproduced deterministically.

CI integration¶

CI pipelines can:

• pull specific dataset versions,
• run smoke pipelines,
• validate contracts without full retraining.