Track 05Build
3 modules · 2 labs

Data Versioning & DVC

Version large datasets and models alongside code, track data provenance, and reproduce data pipelines.

Assumes: Version Control (Git) and Linux fundamentals.

Modules

  1. Why Traditional Git Fails for Large Datasets
  2. Setting Up Data Version Control (DVC) with Cloud Storage Backends
  3. Reproducing Data Pipelines and Tracking Artifact Provenance

Tools

  • DVC
  • AWS S3
  • Git
  • Linux
  • Bash

Lab work

Linux shell commands for data handling, DVC initialization, remote storage, and dvc repro pipelines.

 

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Data Versioning & DVC