- A
Use column-level security to hide sensitive columns
Why wrong: Column-level security hides columns but does not filter rows by region.
- B
Use BigQuery row-level access policies
Why wrong: BigQuery does not have built-in row-level access policies; this is not a supported feature.
- C
Create an authorized view that uses SESSION_USER() in a WHERE clause to filter rows
Authorized views can leverage the current user identity to dynamically filter rows, enabling row-level security.
- D
Create separate IAM roles for each region
Why wrong: IAM roles grant access to entire tables, not specific rows.
Quick Answer
The correct answer is to create an authorized view that uses SESSION_USER() in a WHERE clause to filter rows. This is correct because the SESSION_USER() function dynamically returns the email address of the caller running the query, allowing the authorized view to apply row-level security by comparing that identity against a mapping table of users to regions—no table duplication is needed. On the Google Professional Cloud Database Engineer exam, this scenario tests your understanding of how authorized views decouple data access from underlying tables, a common trap being to mistakenly choose table-level access controls or static filters that require separate copies of data. Remember that SESSION_USER() is evaluated at query runtime, not view creation time, making it ideal for multi-tenant environments. Memory tip: Think “SESSION_USER() = security per session, not per table.”
PCDE Practice Question: Define data structures and implement SQL for Business Intelligence
This PCDE practice question tests your understanding of define data structures and implement sql for business intelligence. 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.
A BI manager needs to restrict access to sensitive sales data so that salespeople can only see their own region's data. Which BigQuery feature should be used to implement row-level security without duplicating tables?
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 an authorized view that uses SESSION_USER() in a WHERE clause to filter rows
Option C is correct because an authorized view with SESSION_USER() in a WHERE clause dynamically filters rows based on the caller's identity, providing row-level security without duplicating tables. This approach leverages BigQuery's ability to share a single view with different users, each seeing only their authorized subset of data, which aligns with the requirement to restrict salespeople to their own region's data.
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.
- ✗
Use column-level security to hide sensitive columns
Why it's wrong here
Column-level security hides columns but does not filter rows by region.
- ✗
Use BigQuery row-level access policies
Why it's wrong here
BigQuery does not have built-in row-level access policies; this is not a supported feature.
- ✓
Create an authorized view that uses SESSION_USER() in a WHERE clause to filter rows
Why this is correct
Authorized views can leverage the current user identity to dynamically filter rows, enabling row-level security.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Create separate IAM roles for each region
Why it's wrong here
IAM roles grant access to entire tables, not specific rows.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse 'row-level access policies' (a conceptual term) with a native BigQuery feature, leading them to select Option B, when in fact BigQuery implements row-level security through authorized views with SESSION_USER() or similar dynamic filtering, not a dedicated policy object.
Detailed technical explanation
How to think about this question
Under the hood, SESSION_USER() returns the email of the authenticated user running the query, which can be joined to a mapping table (e.g., user_region) to filter rows dynamically. This pattern avoids table duplication and leverages BigQuery's shared dataset model, where the view is authorized via a separate dataset's authorized views list, ensuring the underlying table remains private. A real-world scenario is a multinational company where sales managers in different countries query the same sales table but see only their country's data, with the mapping table maintained in a separate, secure dataset.
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.
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FAQ
Questions learners often ask
What does this PCDE question test?
Define data structures and implement SQL for Business Intelligence — This question tests Define data structures and implement SQL for Business Intelligence — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Create an authorized view that uses SESSION_USER() in a WHERE clause to filter rows — Option C is correct because an authorized view with SESSION_USER() in a WHERE clause dynamically filters rows based on the caller's identity, providing row-level security without duplicating tables. This approach leverages BigQuery's ability to share a single view with different users, each seeing only their authorized subset of data, which aligns with the requirement to restrict salespeople to their own region's data.
What should I do if I get this PCDE 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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Last reviewed: Jun 25, 2026
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