lakeFS

Step 1: Create a branch for each experiment.

Step 2: Train the model on the data in the branch.

Step 3: Record the data version used for training.

Step 4: Revert to the same data version to reproduce the experiment.

Step 1: Create a branch from the main branch.

Step 2: Apply data quality checks on the data in the branch.

Step 3: Fix any data quality issues identified.

Step 4: Merge the branch back into the main branch after the tests pass.

Step 1: Regularly back up the lakeFS repository.

Step 2: Monitor the data for corruption or errors.

Step 3: Identify the last known good version of the data.

Step 4: Revert the lakeFS repository to that version.

Step 1: Create a branch for each engineer or feature.

Step 2: Develop the pipeline logic in the branch.

Step 3: Test the pipeline in the branch.

Step 4: Merge the branches back into the main branch after testing.

Step 1: Track all data changes in lakeFS.

Step 2: Store the data lineage information.

Step 3: Generate audit reports.

Step 4: Review and approve the audit reports.