Question 203 of 500
Ensuring successful operation of a cloud solutionmediumMultiple ChoiceObjective-mapped

Google ACE Practice Question: Ensuring successful operation of a cloud solution

This ACE practice question tests your understanding of ensuring successful operation of a cloud solution. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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 analytics. They notice that queries are slow and expensive. The data is loaded daily into a single table. Which action would most improve performance and reduce cost?

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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 date and cluster by frequently filtered columns.

Partitioning the table by date allows BigQuery to prune partitions during query execution, scanning only the relevant daily data instead of the entire table. Clustering on frequently filtered columns further reduces the data scanned by sorting data within partitions. This directly reduces both query cost (pay-per-byte) and latency, addressing the core issue of slow, expensive queries on a large daily-loaded table.

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 a flat-rate reservation to improve query concurrency.

    Why it's wrong here

    Flat-rate controls slot usage but doesn't improve individual query performance.

  • Denormalize the table to reduce joins.

    Why it's wrong here

    Can reduce join overhead but may increase storage cost; less effective than partitioning.

  • Increase the number of slots available for the project.

    Why it's wrong here

    More slots increase concurrency but not per-query performance.

  • Partition the table by date and cluster by frequently filtered columns.

    Why this is correct

    Partitioning prunes partitions, clustering improves filter efficiency, reducing scanned data.

    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 misconception that increasing compute resources (slots or concurrency) is the primary fix for slow queries, when in reality data pruning via partitioning and clustering is the first and most impactful optimization for cost and performance.

Detailed technical explanation

How to think about this question

BigQuery charges based on the number of bytes processed by each query (on-demand pricing). Partitioning by date creates separate storage blocks for each day, and clustering physically reorders data within partitions based on column values (e.g., user_id, region). When a query filters on the partition column (e.g., date) and a clustered column, BigQuery uses the table's metadata to skip entire blocks of data, achieving sub-second scan times on petabyte-scale tables. This is a fundamental optimization for time-series data, as daily loads naturally align with date-based partitioning.

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.

What to study next

Got this wrong? Here's your next step.

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

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FAQ

Questions learners often ask

What does this ACE question test?

Ensuring successful operation of a cloud solution — This question tests Ensuring successful operation of a cloud solution — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: Partition the table by date and cluster by frequently filtered columns. — Partitioning the table by date allows BigQuery to prune partitions during query execution, scanning only the relevant daily data instead of the entire table. Clustering on frequently filtered columns further reduces the data scanned by sorting data within partitions. This directly reduces both query cost (pay-per-byte) and latency, addressing the core issue of slow, expensive queries on a large daily-loaded table.

What should I do if I get this ACE 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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Last reviewed: Jun 30, 2026

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This ACE 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 ACE exam.