PCSE Ensuring Data Protection Practice Question
A company uses Cloud DLP to inspect BigQuery tables for sensitive data. They want to automatically de-identify the data as it is inserted into a new table using a DLP de-identification template. Which approach should they use?
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
✓
Create a DLP de-identification template and apply it to the BigQuery table using a DLP job.
Cloud DLP can be used to create a de-identification template and then apply it to data in BigQuery via a DLP job or by using the DLP API to transform data on the fly. However, to automatically de-identify data as it is inserted, a common pattern is to use Cloud Functions triggered by BigQuery streaming inserts or scheduled DLP jobs that transform the data and write to a new table.
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 Audit Logs to monitor insertions and manually run a DLP transformation.
Why it's wrong here
This is not automated and does not meet the requirement.
- ✗
Use Cloud DLP inspection job triggers to scan the table and send notifications.
Why it's wrong here
Inspection only detects sensitive data; it does not de-identify.
- ✓
Create a DLP de-identification template and apply it to the BigQuery table using a DLP job.
Why this is correct
A DLP de-identification job can read from the source table, apply the template, and write the de-identified data to a destination table.
- ✗
Use BigQuery column-level security with data masking rules.
Why it's wrong here
Masking rules do not transform the underlying data; they only mask it at query time.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This PCSE 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 PCSE exam.