This PCDE practice question tests your understanding of define data structures and implement sql for business intelligence. 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 uses BigQuery BI Engine for sub-second query performance. However, some queries are hitting the BI Engine memory limit. Which action should be taken?
Cluster the tables more granularly.
Why wrong: Clustering improves scan efficiency but does not increase memory limit.
Increase BI Engine capacity allocation.
Allocating more memory to BI Engine allows caching larger datasets.
Use a reservation with a higher slot count.
Why wrong: Slots are compute resources, not BI Engine memory.
Optimize the dimension tables by denormalizing.
Why wrong: Denormalization increases memory footprint.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Increase BI Engine capacity allocation.
BI Engine is an in-memory analysis service that accelerates queries by caching data in memory. When queries exceed the allocated memory, they spill to disk, causing performance degradation. Increasing the BI Engine capacity allocation directly addresses this by providing more memory for caching, enabling sub-second query performance for larger datasets.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Cluster the tables more granularly.
Why it's wrong here
Clustering improves scan efficiency but does not increase memory limit.
Increase BI Engine capacity allocation.
Why this is correct
Allocating more memory to BI Engine allows caching larger datasets.
Related concept
Read the scenario before looking for a memorised answer.
Use a reservation with a higher slot count.
Why it's wrong here
Slots are compute resources, not BI Engine memory.
Optimize the dimension tables by denormalizing.
Why it's wrong here
Denormalization increases memory footprint.
Common exam traps
Google Cloud often tests the misconception that increasing slot count (compute) solves memory bottlenecks, but BI Engine memory is a separate resource that must be explicitly allocated; candidates confuse slot-based reservations with in-memory caching.
Detailed technical explanation
BI Engine uses a columnar in-memory cache that stores frequently accessed data from BigQuery tables. When the cache is full, BI Engine evicts older or less-used data using an LRU policy, and queries that require evicted data must re-read from disk, increasing latency. The BI Engine capacity allocation is set at the project level in the BigQuery admin console, measured in GB, and can be increased up to a maximum of 50% of the project's total slot capacity, with a hard limit of 100 GB per project by default (adjustable via quota increase request).
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
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FAQ
Define data structures and implement SQL for Business Intelligence — This question tests Define data structures and implement SQL for Business Intelligence — Read the scenario before looking for a memorised answer..
The correct answer is: Increase BI Engine capacity allocation. — BI Engine is an in-memory analysis service that accelerates queries by caching data in memory. When queries exceed the allocated memory, they spill to disk, causing performance degradation. Increasing the BI Engine capacity allocation directly addresses this by providing more memory for caching, enabling sub-second query performance for larger datasets.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 30, 2026
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