hardMultiple Choice
Cloud Digital Leader Practice Question: A global enterprise must store customer data in…
A global enterprise must store customer data in specific geographic regions to comply with data residency laws. They also need to be able to analyze data across all regions without centralizing it. Which approach best balances compliance and analytics?
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 regional Cloud Storage buckets per region and BigQuery with federated queries.
Regional Cloud Storage buckets keep each region's customer data physically within its required geography, satisfying data residency laws, while BigQuery federated queries (external tables over Cloud Storage) let analysts query that data in place across regions without copying or centralizing it. This combination preserves compliance and enables cross-regional analytics. Option A does not provide a cross-region analytics mechanism and would require custom data movement or query federation, adding complexity and risk. Option C centralizes all data in one region, directly violating residency requirements. Option D uses a multi-region bucket, which may replicate data outside the mandated region and thus fails the residency constraint.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Deploy identical Compute Engine instances with databases in each region.
Why it's wrong here
Identical regional Compute Engine databases create independent silos with no cross-region query layer, so analysing across all regions requires bespoke federation or copying, which centralises data. It is tempting when teams need low-latency local writes, but the stem demands distributed analytics without centralisation.
- ✓
Use regional Cloud Storage buckets per region and BigQuery with federated queries.
Why this is correct
Regional buckets keep each region's data physically resident, satisfying data residency law, while BigQuery federated queries read across those external buckets without copying or centralising data. This delivers cross-region analytics while preserving the compliance constraint the stem requires.
- ✗
Store all data in a single region and use Cloud CDN for fast access.
Why it's wrong here
A single region plus Cloud CDN still stores all customer data in one jurisdiction, violating residency for every other region, and CDN caches only HTTP content, not analytical datasets. It is tempting for read-heavy web delivery, but it cannot satisfy per-region storage mandates.
- ✗
Use a single Cloud Storage multi-region bucket with granular access controls.
Why it's wrong here
A multi-region bucket places data in Google-selected locations outside the customer's chosen regions, breaching residency requirements. It is tempting because multi-region buckets maximise durability and low-latency access, which suits non-regulated global workloads, but residency law forbids that placement here.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
Go deeper
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Key term
General Data Protection Regulation
A European Union law that gives individuals control over their personal data and sets strict rules for how organizations collect, store, and process that data.
Key term
BigQuery
BigQuery is a fully managed, serverless data warehouse on Google Cloud that lets you run fast SQL queries on massive datasets without managing any infrastructure.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This GCDL 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 GCDL exam.