- A
Use Cloud Dataflow to tokenize the data during ingestion into BigQuery.
Why wrong: Dataflow transforms the data before storage, requiring changes to downstream queries.
- B
Use Cloud DLP integration with BigQuery via SQL functions like `DLP_TOKENIZE`.
BigQuery's `DLP_TOKENIZE` function allows pseudonymization at query time, minimizing changes to existing SQL.
- C
Use Cloud KMS to encrypt the data at rest.
Why wrong: Cloud KMS encrypts data but does not pseudonymize; queries would still see encrypted blobs.
- D
Use Cloud Functions to tokenize data after loading into BigQuery.
Why wrong: Cloud Functions can process data but require additional orchestration and may not be real-time.
Question 45 of 985
PCSE Supporting Compliance Requirements Practice Question
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 is implementing GDPR compliance and wants to ensure that personal data is pseudonymized in BigQuery. They plan to use Cloud DLP to tokenize data before loading. Which approach should they take to minimize changes to existing SQL queries?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"minimum / minimize"Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
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
✓
Use Cloud DLP integration with BigQuery via SQL functions like `DLP_TOKENIZE`.
BigQuery has built-in functions like `DLP_TOKENIZE` that can be used in SQL queries to tokenize data on the fly without changing the schema. This allows pseudonymization while preserving the ability to query. Pre-processing with Dataflow would change the way data is stored and require modifications to queries. Using Cloud Functions adds complexity. Cloud KMS does not tokenize.
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 Cloud Dataflow to tokenize the data during ingestion into BigQuery.
Why it's wrong here
Dataflow transforms the data before storage, requiring changes to downstream queries.
- ✓
Use Cloud DLP integration with BigQuery via SQL functions like `DLP_TOKENIZE`.
Why this is correct
BigQuery's `DLP_TOKENIZE` function allows pseudonymization at query time, minimizing changes to existing SQL.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use Cloud KMS to encrypt the data at rest.
Why it's wrong here
Cloud KMS encrypts data but does not pseudonymize; queries would still see encrypted blobs.
- ✗
Use Cloud Functions to tokenize data after loading into BigQuery.
Why it's wrong here
Cloud Functions can process data but require additional orchestration and may not be real-time.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- 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 cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
What to study next
Got this wrong? Here's your next step.
Identify which PCSE exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
- →
Supporting Compliance Requirements — study guide chapter
Learn the concepts, then practise the questions
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Supporting Compliance Requirements practice questions
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FAQ
Questions learners often ask
What does this PCSE question test?
Supporting Compliance Requirements — This question tests Supporting Compliance Requirements — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use Cloud DLP integration with BigQuery via SQL functions like `DLP_TOKENIZE`. — BigQuery has built-in functions like `DLP_TOKENIZE` that can be used in SQL queries to tokenize data on the fly without changing the schema. This allows pseudonymization while preserving the ability to query. Pre-processing with Dataflow would change the way data is stored and require modifications to queries. Using Cloud Functions adds complexity. Cloud KMS does not tokenize.
What should I do if I get this PCSE question wrong?
Identify which PCSE exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Are there clue words in this question I should notice?
Yes — watch for: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
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Last reviewed: Jul 4, 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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