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PMLE Practice Question: A data science team uses a shared Cloud Storage…
A data science team uses a shared Cloud Storage bucket to store training datasets. They notice that some team members accidentally overwrite existing datasets, causing issues with reproducibility. Which approach best prevents accidental overwrites while maintaining collaboration?
⚠ Common exam trap
Candidates often think IAM roles or permissions are the only way to control data integrity, overlooking that object versioning provides a safety net without blocking collaboration.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Enable object versioning on the bucket and use lifecycle rules to manage versions.
Enabling object versioning on a Cloud Storage bucket preserves all versions of an object, so even if a team member overwrites a dataset, the previous version remains accessible. This maintains collaboration (anyone can upload) while preventing permanent data loss. Lifecycle rules can then be used to manage storage costs by automatically deleting old versions after a specified period.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use a single shared service account with strict IAM roles that allow only append operations.
Why it's wrong here
Cloud Storage IAM cannot express append-only semantics; permissions are bucket- or object-level, so write access still permits overwriting existing objects. Object Versioning preserves each upload as a distinct generation, preventing destructive overwrites. A shared service account with restricted roles suits centralised automation, not collaborative dataset protection.
- ✗
Require team members to manually rename files before uploading.
Why it's wrong here
Manual renaming relies on human discipline, so overwrites still occur whenever someone forgets; it enforces nothing technically. Object Versioning is the mechanism that preserves every write, letting collaborators upload freely while retaining prior dataset versions for reproducibility. Renaming suits ad-hoc personal files, not shared datasets needing guaranteed immutability.
- ✗
Set bucket permissions to read-only for all team members except the data owner.
Why it's wrong here
Read-only permissions block every member from writing, so nobody can upload new datasets or correct existing ones, breaking collaboration. It is tempting because it stops overwrites, and would be correct for an archive bucket where consumers only read published data, not a shared working store.
- ✓
Enable object versioning on the bucket and use lifecycle rules to manage versions.
Why this is correct
Object versioning preserves every overwrite as a noncurrent version, so prior datasets remain retrievable and reproducibility is maintained. Lifecycle rules then prune aged versions to control storage cost. This directly satisfies the stem's constraint of preventing accidental overwrites while keeping the bucket shared for collaboration.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This PMLE practice question is part of Courseiva's free Google Cloud certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the PMLE exam.