The answer is to use BigQuery column-level security to restrict access to sensitive columns. This method works by applying access policies directly to specific columns within a table, allowing you to control which users or roles can view sensitive data like PII or financial records without duplicating tables or creating views. On the Google Professional Cloud Architect exam, this question tests your understanding of data governance and access control within BigQuery, often appearing alongside topics like Cloud DLP de-identification transforms and authorized views. A common trap is confusing row-level security with column-level security—remember that column-level security protects vertical slices of data, while row-level security filters horizontal rows. For the exam, pair this with Cloud DLP during ingestion to automatically mask or tokenize sensitive data before it reaches storage, ensuring protection at rest. Memory tip: think "columns for categories, rows for conditions" to keep the distinction clear.
Google PCA Design for security and compliance Practice Question
This PCA practice question tests your understanding of design for security and compliance. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
Which THREE are valid methods to protect sensitive data in BigQuery?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Apply Cloud DLP de-identification transforms during data ingestion.
Cloud DLP de-identification transforms can be applied during data ingestion to automatically mask, tokenize, or redact sensitive data before it is stored in BigQuery. This ensures that sensitive information is protected at rest and is not accessible to unauthorized users, aligning with data security best practices.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
Enable customer-managed encryption keys (CMEK) to encrypt sensitive columns.
Why it's wrong here
CMEK encrypts the entire table, not individual columns.
✓
Apply Cloud DLP de-identification transforms during data ingestion.
Why this is correct
Cloud DLP can automatically de-identify data before loading into BigQuery.
Related concept
Read the scenario before looking for a memorised answer.
✓
Create authorized views that query only non-sensitive columns.
Why this is correct
Authorized views can share query results without exposing underlying tables.
Related concept
Read the scenario before looking for a memorised answer.
✓
Use BigQuery column-level security to restrict access to sensitive columns.
Why this is correct
Column-level security allows you to restrict access to specific columns.
Related concept
Read the scenario before looking for a memorised answer.
✗
Use IAM roles to grant access at the dataset level, which automatically masks sensitive data.
Why it's wrong here
IAM roles do not provide data masking; they control access to datasets.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse encryption (CMEK) with data masking or de-identification, assuming that encrypting the entire dataset protects sensitive columns, when in fact column-level security or DLP transforms are required for granular protection.
Detailed technical explanation
How to think about this question
Cloud DLP integrates with BigQuery via the Data Loss Prevention API, allowing you to define inspection templates and de-identification templates that can be applied during data ingestion using Cloud Dataflow or Cloud Functions. This enables real-time transformation of sensitive fields such as credit card numbers or social security numbers into formats like tokenized values or hashed strings, ensuring compliance with regulations like GDPR or PCI DSS.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A company's IT admin needs to give a contractor read-only access to production logs without sharing account credentials. Using role-based access control (RBAC) and temporary scoped permissions — not a permanent shared password — is the correct pattern. Questions like this test whether you can apply least-privilege access across cloud identity services.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this PCA question in full detail.
Design for security and compliance — This question tests Design for security and compliance — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Apply Cloud DLP de-identification transforms during data ingestion. — Cloud DLP de-identification transforms can be applied during data ingestion to automatically mask, tokenize, or redact sensitive data before it is stored in BigQuery. This ensures that sensitive information is protected at rest and is not accessible to unauthorized users, aligning with data security best practices.
What should I do if I get this PCA question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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