hardMultiple ChoiceObjective-mapped
PDE Practice Question: A financial services company must comply with…
A financial services company must comply with GDPR "right to be forgotten". They store customer transactions in BigQuery partitioned by date. When a user requests deletion, all their data must be removed within 48 hours. The deletion requests are received via a Pub/Sub topic. What is the most scalable and cost-effective approach?
⚠ Common exam trap
Google Cloud often tests the misconception that BigQuery DELETE statements are the simplest way to remove data, but the trap here is that DELETE operations on large partitioned tables are expensive and not scalable for streaming deletion requests, whereas a Dataflow-based rewrite is both cost-effective and meets the 48-hour SLA.
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
✓
Use a Dataflow pipeline that reads the deletion IDs from Pub/Sub, joins with the transactions table using a side input, and writes the filtered data to a new table, then swapping
It uses Dataflow to process deletion requests from Pub/Sub, join them with the BigQuery transactions table via a side input, and write a filtered copy to a new table. This approach is scalable (handles high-throughput streaming deletions) and cost-effective (avoids expensive DELETE mutations on BigQuery, which consume slot resources and can be slow for large tables). Swapping the new table for the old one completes the deletion efficiently within the 48-hour SLA.
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 Cloud Functions to execute a BigQuery DELETE statement on each request
Why it's wrong here
Each DELETE scans the entire table, which is costly and slow for large tables.
- ✗
Use Cloud DLP to redact the user's data in Cloud Storage
Why it's wrong here
Cloud DLP is for data loss prevention, not deletion from BigQuery.
- ✓
Use a Dataflow pipeline that reads the deletion IDs from Pub/Sub, joins with the transactions table using a side input, and writes the filtered data to a new table, then swapping
Why this is correct
This scales well and avoids full table scans; the side input contains the IDs to delete.
- ✗
Use BigQuery table snapshots and restore after deletion
Why it's wrong here
Snapshots are for point-in-time recovery, not selective deletion; restoring would undo other deletions.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This PDE 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 PDE exam.