PDE Preparing and Using Data for Analysis Practice Question
You are building a multi-cloud analytics solution to join data from Google Cloud and AWS S3. You need to query the S3 data using BigQuery without moving it. Which Google Cloud service should you use?
⚠ Common exam trap
The trap is confusing data transfer services with query-in-place services, leading to picking BigQuery Data Transfer Service.
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
✓
BigQuery Omni
BigQuery Omni is the service that allows querying data in AWS S3 directly from BigQuery without moving it. It deploys BigQuery compute in AWS to process the data locally, returning results to Google Cloud.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Looker
Why it's wrong here
Looker is a BI and visualisation layer that queries modelled data; it cannot itself federate or query external S3 objects from BigQuery. It is tempting because Looker sits on BigQuery, but the requirement is external query access, which BigQuery Omni provides.
- ✗
Dataproc
Why it's wrong here
Dataproc runs Spark and Hadoop clusters for processing; it does not provide BigQuery SQL access to external S3 objects. It is tempting because Dataproc handles cross-cloud data pipelines, but the requirement is querying S3 directly from BigQuery, which BigQuery Omni enables.
- ✗
BigQuery Data Transfer Service
Why it's wrong here
BigQuery Data Transfer Service schedules recurring copies of external data into BigQuery; it moves data rather than querying S3 in place. It is tempting because it connects BigQuery to external sources, but the stem explicitly forbids moving the data, which BigQuery Omni satisfies.
- ✓
BigQuery Omni
Why this is correct
BigQuery Omni runs BigQuery queries directly against AWS S3 and Azure Blob Storage via Anthos-hosted compute, returning results without extracting or duplicating the data. This satisfies the stem's requirement to join Google Cloud and S3 data while querying S3 in place, avoiding egress and movement costs.
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 |
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JA
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.