easyMultiple ChoiceObjective-mapped
PDE Practice Question: Building a data lake on Cloud Storage for log…
A company is building a data lake on Cloud Storage for log analysis. Log files (CSV) arrive every 5 minutes from multiple sources. The files should be ingested into BigQuery for reporting within 15 minutes. Which approach best meets the requirements with minimal operational overhead?
⚠ Common exam trap
Google Cloud often tests the misconception that serverless options like Cloud Functions are only for simple tasks, but here they are the most efficient choice for near-real-time ingestion with minimal overhead, while Dataflow is overkill for this straightforward file-load pattern.
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
✓
Set up a Cloud Storage notification to trigger a Cloud Function that loads each file into BigQuery using the BigQuery API.
Cloud Storage notifications trigger a Cloud Function on each file upload, which then loads the file into BigQuery via the BigQuery API. This provides near-real-time ingestion (within seconds of file arrival) with minimal operational overhead, as there are no servers to manage and no scheduling needed. The 5-minute file arrival and 15-minute SLA are easily met without complex infrastructure.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Set up a Cloud Storage notification to trigger a Cloud Function that loads each file into BigQuery using the BigQuery API.
Why this is correct
This approach provides near-real-time loading (within minutes) with minimal operational overhead, as Cloud Functions are serverless.
- ✗
Schedule a daily batch load from Cloud Storage to BigQuery using the BigQuery Data Transfer Service.
Why it's wrong here
Daily batch does not meet the 15-minute freshness requirement.
- ✗
Use Dataflow to read from Pub/Sub (ingested from Cloud Storage) and write to BigQuery.
Why it's wrong here
Adding Pub/Sub and Dataflow introduces unnecessary complexity and cost for this simple CSV-to-BigQuery pipeline.
- ✗
Use BigQuery federated queries to query the CSV files directly from Cloud Storage.
Why it's wrong here
Federated queries have limited performance and are not suitable for frequent interactive queries; also, they don't load data into BigQuery.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.