PDE Designing Data Processing Systems Practice Question
A company has a BigQuery dataset containing sensitive customer data. They want to share a subset of this data with external partners, ensuring that partners can only see specific columns and rows. Which BigQuery feature should they use?
⚠ Common exam trap
PDE often tests the misconception that dataset-level permissions or materialized views provide fine-grained sharing — candidates pick dataset access controls when the requirement is column/row filtering, which only authorized views deliver.
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
✓
Authorized views
Authorized views in BigQuery allow a view to be created in one dataset that reads from a source dataset, and then access to the view is granted to external partners without granting access to the underlying source data. This enables column- and row-level filtering (via the view's SQL) so partners see only the permitted subset. This is the standard BigQuery pattern for sharing restricted data.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Materialized views
Why it's wrong here
Materialized views precompute and cache query results for performance; they do not enforce row-level or column-level visibility for external partners. It is tempting as a way to expose a curated result set, and it would be correct for accelerating repeated aggregate queries.
- ✓
Authorized views
Why this is correct
Authorized views grant external partners query access to a view while restricting them to the columns and rows the view exposes, without granting underlying table access. This directly satisfies the requirement to share only a subset of sensitive customer data.
- ✗
Clustered tables
Why it's wrong here
Clustered tables physically co-locate rows sharing column values to speed filtered queries; they do not restrict which columns or rows a partner can read. It is tempting as a performance and data-organisation feature, and it would be correct for optimising query cost on frequently filtered columns.
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Dataset-level access controls
Why it's wrong here
Dataset-level access controls grant or deny access to the whole dataset, so partners would see every column and row rather than the permitted subset. It is tempting because it is the native sharing mechanism, and it would be correct when a partner needs full access to an entire dataset.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Google Cloud exam blueprint
This PDE 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 PDE exam.