Google PCA Practice Question: Analysing and Optimising Technical and Business Processes
A company's BigQuery costs are higher than expected. They run many ad-hoc queries with filters on the 'transaction_date' column and 'customer_id' column. They also have a materialized view that is rarely used. Which combination of actions will MOST effectively reduce query costs?
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 on transaction_date, cluster on customer_id, and drop the unused materialized view
Partitioning by transaction_date reduces scanned data for date filters. Clustering by customer_id further reduces bytes billed for queries filtering on that column. Dropping unused materialized views avoids storage costs.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Convert to a clustered table on transaction_date and disable caching
Why it's wrong here
Disabling caching would increase costs by requiring re-scans. Clustering alone may not suffice.
- ✗
Use flat-rate pricing for all queries and cluster on transaction_date
Why it's wrong here
Flat-rate pricing is a reservation model; clustering alone may not reduce costs for ad-hoc queries if not aligned with filters.
- ✗
Partition on customer_id and use materialized views for all queries
Why it's wrong here
Partitioning on customer_id is less effective for date-range queries; materialized views increase storage cost.
- ✓
Partition on transaction_date, cluster on customer_id, and drop the unused materialized view
Why this is correct
Partitioning and clustering reduce bytes scanned; dropping unused views cuts storage costs.
Go deeper
Related to this question
Learn chapter
Cloud Storage: Objects and Buckets
Key term
Column
A column is a vertical set of values in a database table that stores one specific type of attribute for every row.
Key term
Data
Data is raw, unprocessed information, like numbers, words, or measurements, that can be stored, processed, and analyzed by computers.
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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.