This PCSE practice question tests your understanding of supporting compliance requirements. 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 company needs to comply with GDPR and must implement data subject access request (DSAR) capabilities. Which TWO Google Cloud services should they use to locate and export personal data across various data stores?
Cloud Key Management Service (KMS)
Why wrong: KMS handles encryption, not data discovery.
Cloud Storage
Why wrong: Cloud Storage is a target but not for locating personal data.
BigQuery
BigQuery can store and query personal data for DSAR responses.
Cloud Data Loss Prevention (DLP)
DLP can inspect and classify personal data across storage and BigQuery.
VPC Service Controls
Why wrong: Controls perimeter security, not data location.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
BigQuery
BigQuery is correct because it can be used to query and export personal data stored in BigQuery tables via SQL, enabling DSAR compliance by locating and extracting data subject information. Cloud Data Loss Prevention (DLP) is correct because it can inspect and classify personal data across various Google Cloud data stores (including Cloud Storage, BigQuery, and Datastore) and de-identify or export findings, directly supporting DSAR workflows.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Cloud Key Management Service (KMS)
Why it's wrong here
KMS handles encryption, not data discovery.
Cloud Storage
Why it's wrong here
Cloud Storage is a target but not for locating personal data.
BigQuery
Why this is correct
BigQuery can store and query personal data for DSAR responses.
Related concept
Read the scenario before looking for a memorised answer.
Cloud Data Loss Prevention (DLP)
Why this is correct
DLP can inspect and classify personal data across storage and BigQuery.
Related concept
Read the scenario before looking for a memorised answer.
VPC Service Controls
Why it's wrong here
Controls perimeter security, not data location.
Common exam traps
Google Cloud often tests the misconception that Cloud Storage or VPC Service Controls can handle DSARs, but they are storage and security boundary services respectively, not data discovery or export tools; candidates confuse data storage with data subject access request capabilities.
Detailed technical explanation
BigQuery supports INFORMATION_SCHEMA and SQL queries to find and export rows containing personal identifiers, while DLP uses built-in infoType detectors (e.g., EMAIL_ADDRESS, PERSON_NAME) to scan data at rest across services like Cloud Storage, BigQuery, and Datastore. DLP can output findings to BigQuery or Cloud Storage for audit trails, and its inspection jobs can be configured to run on schedules or on-demand for DSAR requests. Under the hood, DLP uses machine learning and pattern matching to identify sensitive data, and its de-identification transforms (e.g., masking, tokenization) can be applied before export to comply with data minimization principles.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
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FAQ
Supporting compliance requirements — This question tests Supporting compliance requirements — Read the scenario before looking for a memorised answer..
The correct answer is: BigQuery — BigQuery is correct because it can be used to query and export personal data stored in BigQuery tables via SQL, enabling DSAR compliance by locating and extracting data subject information. Cloud Data Loss Prevention (DLP) is correct because it can inspect and classify personal data across various Google Cloud data stores (including Cloud Storage, BigQuery, and Datastore) and de-identify or export findings, directly supporting DSAR workflows.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 30, 2026
This PCSE 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 PCSE exam.
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