ML Data Versioning
Your model broke. Was it a code change or a data change? Without data versioning, you'll never know. We implement data version control so every training dataset is tracked, every change is auditable, and any historical state is reproducible — the same rigor you apply to code, applied to data.
Need this done for your project?
We implement, you ship. Async, documented, done in days.
Tool Selection
DVC (Data Version Control) for teams that want Git-like workflows for data — dvc push/pull, branch-based data versions. LakeFS for teams with data lake architectures — Git-like branching on S3-compatible storage. Delta Lake or Iceberg for teams already on Spark with time-travel needs. We pick based on your storage backend, team workflow, and data volume. Each tool has different scaling characteristics.
Versioning Workflow
Datasets get versioned alongside code. A training pipeline references a specific data version (DVC hash, LakeFS commit, or Delta version). Data changes go through a review process — data PRs with distribution diffs, schema change summaries, and sample comparisons. Merging a data PR triggers downstream pipeline runs. No more 'someone updated the CSV on S3 and everything broke'.
Storage & Performance
DVC uses content-addressable storage with deduplication — unchanged files don't get re-uploaded. LakeFS provides copy-on-write branching with zero storage overhead for unchanged data. We configure remote storage (S3, GCS, Azure Blob) with proper lifecycle policies. Large datasets get chunked for parallel transfer. Storage costs stay proportional to actual data changes, not total dataset size.
Integration with ML Pipelines
Training pipelines reference data versions explicitly — 'train on dataset v2.3.1'. Feature store materialization jobs tag output with the source data version. Model registry entries link back to the training data version. This creates full lineage: production model → training run → code commit + data version → raw data sources. Debugging model issues means tracing this chain, not guessing.
Why Anubiz Engineering
Ready to get started?
Skip the research. Tell us what you need, and we'll scope it, implement it, and hand it back — fully documented and production-ready.