Google PCA Manage implementation of cloud architecture Practice Question
Which THREE actions can help reduce costs for a BigQuery workload that runs frequent, ad-hoc analytical queries on a large dataset?
⚠ Common exam trap
Google Cloud often tests the distinction between cost-reduction techniques that reduce bytes scanned (partitioning, clustering, materialized views) versus pricing model choices (flat-rate vs. on-demand), leading candidates to mistakenly select flat-rate pricing as a cost-saving action for ad-hoc queries.
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
✓
Partition the table by a date or timestamp column.
Partitioning the table by a date or timestamp column (Option B) reduces the amount of data scanned by BigQuery for queries that filter on that column, directly lowering query costs (pay-per-byte model). It also improves performance by pruning irrelevant partitions, making it a core cost-saving technique for ad-hoc analytical workloads.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Enable automatic schema detection to avoid manual schema definition.
Why it's wrong here
Auto-schema doesn't reduce cost; it may cause inefficiencies.
- ✓
Partition the table by a date or timestamp column.
Why this is correct
Partitioning allows query pruning, scanning only relevant partitions.
- ✓
Create materialized views for common aggregation queries.
Why this is correct
Materialized views avoid recomputation, reducing cost.
- ✓
Use clustering on columns frequently used in filter clauses.
Why this is correct
Clustering organizes data, reducing bytes processed.
- ✗
Use flat-rate pricing with reserved slots.
Why it's wrong here
Flat-rate is for predictable costs, not necessarily reducing cost; may increase if underutilized.
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This PCA 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 PCA exam.