Google PCA Practice Question: Analyze and optimize technical and business processes
A company is using BigQuery for data analytics. They want to optimize costs while maintaining query performance. Which TWO actions should they take? (Choose 2.)
⚠ Common exam trap
Google Cloud often tests the distinction between cost optimization and performance optimization, and the trap here is that candidates might choose reserved slots (Option A) thinking it always reduces costs, when in fact it is a pricing model that only benefits sustained high usage, not a direct cost-reduction technique for typical query patterns.
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 tables by date.
Partitioning tables by date (Option C) is correct because it allows BigQuery to prune partitions during query execution, scanning only the relevant date ranges instead of the entire table. This reduces the amount of data processed, directly lowering query costs under on-demand pricing while maintaining performance through reduced I/O.
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 reserved slots with flat-rate pricing.
Why it's wrong here
Reserved slots are useful for predictable workloads but may not be cost-effective for ad-hoc analytics.
- ✗
Always use SELECT *.
Why it's wrong here
SELECT * scans all columns, increasing costs without benefit.
- ✓
Partition tables by date.
Why this is correct
Partitioning reduces the amount of data scanned, lowering costs.
- ✗
Materialize frequently used queries as tables.
Why it's wrong here
Materialization saves computation but incurs storage costs; it may not be cost-effective for all queries.
- ✓
Use clustering on frequently filtered columns.
Why this is correct
Clustering improves performance and reduces costs by limiting scans to relevant blocks.
Go deeper
Related to this question
Learn chapter
Cloud SQL and Managed Data Stores
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.
Key term
Table
A table is a structured collection of data organized into rows and columns, used in databases and spreadsheets to store and manage information efficiently.
About these practice questions
One of 955 original PCA practice questions on Courseiva, each with a full explanation and wrong-answer analysis — not exam dumps or protected exam content. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.