Crucial Exams

CompTIA DataX DY0-001 (V1) Practice Question

Your organization's GitHub repository contains code for an ML pipeline while the training data (≈200 GB) lives in an Amazon S3 bucket that is overwritten every week. Compliance rules require that anyone who checks out any past Git commit can automatically restore exactly the dataset that was used for that commit, without bloating the repository or exceeding GitHub file-size limits. Which approach best satisfies these requirements?

  • Enable S3 object versioning and save the object version IDs in a YAML configuration file that the pipeline reads at runtime.

  • Store the full dataset in Git Large File Storage so each commit contains a pointer to the data blobs managed by Git LFS.

  • Package every weekly snapshot as a compressed archive and upload it as a GitHub release asset referenced by a repository tag.

  • Track the dataset with DVC: commit the lightweight .dvc pointer files to Git and configure an S3 DVC remote so that "git checkout" followed by "dvc pull" retrieves the exact snapshot.

CompTIA DataX DY0-001 (V1)
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