Google PCA Practice Question: Analyze and optimize technical and business processes
This PCA practice question tests your understanding of analyze and optimize technical and business processes. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
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.)
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.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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.
Related concept
Read the scenario before looking for a memorised answer.
✗
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.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
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.
Detailed technical explanation
How to think about this question
Under the hood, BigQuery's columnar storage and partitioning use a metadata layer to track partition boundaries; when a query includes a filter on the partition column (e.g., _PARTITIONTIME or a date column), the query planner eliminates irrelevant partitions before scanning. Clustering further sorts data within partitions based on specified columns, enabling block-level pruning for highly selective filters, which can reduce bytes read by up to 90% in real-world scenarios with high-cardinality filter columns like user_id or timestamp.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this PCA question in full detail.
Analyze and optimize technical and business processes — This question tests Analyze and optimize technical and business processes — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: 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.
What should I do if I get this PCA question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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