The correct answer is to create a policy tag on the SSN column and bind it to the 'PII_Viewer' role. This works because BigQuery column-level security with policy tags for access control uses taxonomy-based tags to enforce fine-grained access; when a policy tag is applied to a column, only principals granted the `bigquery.dataViewer` access on that specific tag can see the data—others receive NULL or a query error. On the Google Professional Cloud Security Engineer exam, this scenario tests your understanding of how policy tags integrate with IAM to replace legacy views or row-level filters, and a common trap is confusing column-level security with authorized views or table-level IAM. Remember that policy tags are hierarchical and require the `Policy Tag User` role on the taxonomy itself, not just the column. Memory tip: “Tag it, then bag it”—apply the tag to the column, then bind the role to the tag, not the table.
PCSE Ensuring data protection Practice Question
This PCSE practice question tests your understanding of ensuring data protection. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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.
An organization uses BigQuery with column-level security. They have a column containing social security numbers (SSNs) that should only be visible to users with the 'PII_Viewer' role. How should they configure this?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Create a policy tag on the column and bind it to the role.
Option D is correct because BigQuery column-level security uses policy tags to restrict access to sensitive columns. By creating a policy tag on the SSN column and binding it to the 'PII_Viewer' role, only users with that role can see the data; others see NULL or are denied access. This is the native, recommended approach for column-level access control in BigQuery.
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.
✗
Encrypt the column with CMEK and give decrypt permission only to PII_Viewer.
Why it's wrong here
BigQuery does not support per-column encryption natively; also decrypting for each query would be complex.
✗
Use authorized views to filter the column.
Why it's wrong here
Authorized views filter rows, not columns.
✗
Use BigQuery row-level access policies.
Why it's wrong here
Row-level access policies filter rows, not columns.
✓
Create a policy tag on the column and bind it to the role.
Why this is correct
Policy tags implement column-level security in BigQuery.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the distinction between encryption (which protects data at rest but does not control access by role) and policy-based access controls (which enforce visibility at query time), leading candidates to mistakenly choose encryption options for column-level restrictions.
Detailed technical explanation
How to think about this question
Policy tags in BigQuery are managed through Data Catalog and use access control lists (ACLs) bound to IAM roles. When a policy tag is applied to a column, any query against that column by a user without the required role returns NULL or an access-denied error, depending on the tag's access mode. This mechanism works at the storage layer, ensuring that even if a user queries the column directly or via a wildcard, the data is not exposed.
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.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Ensuring data protection — This question tests Ensuring data protection — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Create a policy tag on the column and bind it to the role. — Option D is correct because BigQuery column-level security uses policy tags to restrict access to sensitive columns. By creating a policy tag on the SSN column and binding it to the 'PII_Viewer' role, only users with that role can see the data; others see NULL or are denied access. This is the native, recommended approach for column-level access control in BigQuery.
What should I do if I get this PCSE 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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