- A
Use dataset-level ACLs to deny the partner access to the original table and grant access to a view.
Why wrong: Dataset ACLs are not fine-grained enough to deny access to a specific table while granting access to a view in the same dataset. The partner needs access to the dataset to query the view, which would also expose other tables unless explicitly denied, which is complex and error-prone.
- B
Export the filtered data to a new BigQuery dataset and grant the partner access to that dataset.
Why wrong: This creates a copy of the data that the partner controls. The company loses control over who accesses that copy, and it becomes stale over time.
- C
Create an authorized view in the same dataset, excluding PII columns, and share only the view with the partner's BigQuery account.
Authorized views allow precise control. The view is defined in the dataset and can be shared with specific users. The partner can query the view but cannot access the underlying table, even if they have permissions on the view. The company retains full control.
- D
Create a materialized view and grant the partner the bigquery.dataViewer role on the dataset.
Why wrong: Materialized views are stored tables; granting dataViewer on the dataset would give the partner access to all tables and views in the dataset, including the original table if it's in the same dataset. They could also potentially query the base table directly.
PDE Designing Data Processing Systems Practice Question
This PDE practice question tests your understanding of designing data processing systems. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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 financial services company has a BigQuery dataset containing sensitive customer data. They need to share a subset of this data (excluding PII columns) with an external analytics partner. The partner should be able to query the data using their own BigQuery account, but the company must maintain full control over the underlying table and ensure the partner cannot see or access the original table. 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 an authorized view in the same dataset, excluding PII columns, and share only the view with the partner's BigQuery account.
Authorized views allow you to share a view with specific users/groups while restricting access to the underlying table. The view can be defined to exclude PII columns and can be shared with the partner's account. The partner queries the view directly, but cannot access the base table. This maintains data control and security.
Key principle: ACLs process entries top to bottom and stop at the first match. Entry order and interface direction matter as much as the permit or deny statement.
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 dataset-level ACLs to deny the partner access to the original table and grant access to a view.
Why it's wrong here
Dataset ACLs are not fine-grained enough to deny access to a specific table while granting access to a view in the same dataset. The partner needs access to the dataset to query the view, which would also expose other tables unless explicitly denied, which is complex and error-prone.
- ✗
Export the filtered data to a new BigQuery dataset and grant the partner access to that dataset.
Why it's wrong here
This creates a copy of the data that the partner controls. The company loses control over who accesses that copy, and it becomes stale over time.
- ✓
Create an authorized view in the same dataset, excluding PII columns, and share only the view with the partner's BigQuery account.
Why this is correct
Authorized views allow precise control. The view is defined in the dataset and can be shared with specific users. The partner can query the view but cannot access the underlying table, even if they have permissions on the view. The company retains full control.
Related concept
Standard ACLs match source addresses.
- ✗
Create a materialized view and grant the partner the bigquery.dataViewer role on the dataset.
Why it's wrong here
Materialized views are stored tables; granting dataViewer on the dataset would give the partner access to all tables and views in the dataset, including the original table if it's in the same dataset. They could also potentially query the base table directly.
Common exam traps
Common exam trap: ACLs stop at the first match
ACLs are processed top to bottom. The first matching entry wins, and an implicit deny usually exists at the end.
Detailed technical explanation
How to think about this question
ACL questions test precision: source, destination, protocol, port and direction. A generally correct ACL can still fail if it is applied on the wrong interface or in the wrong direction.
KKey Concepts to Remember
- Standard ACLs match source addresses.
- Extended ACLs can match source, destination, protocol and ports.
- The first matching ACL entry is used.
- There is usually an implicit deny at the end.
TExam Day Tips
- Check inbound versus outbound direction.
- Read the ACL from top to bottom.
- Look for a broader permit or deny above the intended line.
Key takeaway
ACLs process entries top to bottom and stop at the first match. Entry order and interface direction matter as much as the permit or deny statement.
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.
Review ACL processing order, placement rules (standard near destination, extended near source), and inbound vs outbound direction. Study wildcard masks and implicit deny. Then practise related PDE ACL questions on filtering logic and placement.
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FAQ
Questions learners often ask
What does this PDE question test?
Designing Data Processing Systems — This question tests Designing Data Processing Systems — Standard ACLs match source addresses..
What is the correct answer to this question?
The correct answer is: Create an authorized view in the same dataset, excluding PII columns, and share only the view with the partner's BigQuery account. — Authorized views allow you to share a view with specific users/groups while restricting access to the underlying table. The view can be defined to exclude PII columns and can be shared with the partner's account. The partner queries the view directly, but cannot access the base table. This maintains data control and security.
What should I do if I get this PDE question wrong?
Review ACL processing order, placement rules (standard near destination, extended near source), and inbound vs outbound direction. Study wildcard masks and implicit deny. Then practise related PDE ACL questions on filtering logic and placement.
What is the key concept behind this question?
Standard ACLs match source addresses.
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Last reviewed: Jul 4, 2026
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