Roll Back to an Earlier Dataset
Use dvc checkout to reproduce a past data state.
Roll Back to an Earlier Dataset is a free MLOps Academy lesson on CoddyKit — lesson 4 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the MLOps Academy learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.
Why Roll Back at All
Sometimes a new dataset hurts your model, or you need the exact data from last month's experiment. DVC lets you travel back to any past version.
Git Holds the History
Each data version is captured by a committed .dvc file. So your data history lives right inside your normal Git commit history.
git log --oneline data/train.csv.dvcStep One: Move Git Back
First use git checkout to bring back the old .dvc pointer. This rewinds which data version your project expects.
git checkout HEAD~1 data/train.csv.dvcStep Two: Sync the Data
The pointer changed but the file on disk has not yet. Run dvc checkout to update the actual dataset to match the restored pointer.
dvc checkoutThe Two-Step Rule
Rolling back data is always two moves: git checkout changes the pointer, then dvc checkout swaps the data. Skip the second and your data stays stale.
Pull If Data Is Missing
If that old version is not in your local cache, dvc checkout cannot find it. Run dvc pull first to fetch it from the remote, then check out.
dvc pull
dvc checkoutRoll the Whole Project Back
To restore an entire past state, checkout a full commit, then dvc checkout. Code and data jump back to that moment together. ⏪
git checkout v1.0
dvc checkoutTag Important Versions
Give meaningful snapshots a Git tag so they are easy to return to later. Tags turn a cryptic hash into a memorable label.
git tag -a v1.0 -m "Clean baseline dataset"Go Back to the Latest
Done experimenting in the past? Switch your branch forward again and run dvc checkout to restore the newest data. Nothing is lost.
git checkout main
dvc checkoutReproducibility Unlocked
Because any commit maps to an exact dataset, you can reproduce any past result precisely. This is the whole promise of data versioning.
Peek Without Switching
Want one old file without changing branches? dvc get downloads a specific version from a repo into a chosen path, leaving your project untouched.
dvc get <repo-url> data/train.csv --rev v1.0Quick Check
You ran git checkout on an old .dvc file. What must you run next to restore the actual data?
Recap
Rolling back is a two-step dance: git checkout restores the .dvc pointer, then dvc checkout swaps the data to match. Pull first if the old version is not cached.
Frequently asked questions
Is the “Roll Back to an Earlier Dataset” lesson free?
Yes — the full text of “Roll Back to an Earlier Dataset” is free to read here on the web, and the MLOps Academy course includes 4 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the MLOps Academy course, upgrade to CoddyKit PRO.
What will I learn in “Roll Back to an Earlier Dataset”?
Use dvc checkout to reproduce a past data state. You practise MLOps Academy with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.
Do I need any experience to start MLOps Academy?
No prior experience is required. MLOps Academy on CoddyKit is structured for beginners through advanced learners; this is — lesson 4 of 4, so you can start here or from the beginning and move at your own pace.
How long does the “Roll Back to an Earlier Dataset” lesson take?
Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.
Can I write and run code in this MLOps Academy lesson?
Yes. Every MLOps Academy lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.
All lessons in this course
- Why Git Alone Cannot Version Data
- Initialize DVC and Track a Dataset
- Push Data to Remote Storage
- Roll Back to an Earlier Dataset