PCDE Practice Question: Define data structures and implement SQL for Business Intelligence
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.
Which TWO of the following are best practices when designing data structures for business intelligence in BigQuery?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "best"
Why it matters: Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Partition tables on a column that aligns with common filter criteria
Partitioning tables on a column that aligns with common filter criteria (e.g., a date or timestamp column) allows BigQuery to prune partitions during query execution, drastically reducing the amount of data scanned and improving query performance and cost efficiency. This is a core best practice for optimizing BI workloads in BigQuery.
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.
✓
Partition tables on a column that aligns with common filter criteria
Why this is correct
Partitioning limits scanned partitions.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Store raw logs directly in fact tables without any aggregation
Why it's wrong here
Raw logs often need aggregation for BI; direct use is inefficient.
✗
Use NULLable columns extensively to save storage
Why it's wrong here
Nullable columns can complicate queries and do not save significant storage.
✗
Use a single wide table for all data to simplify schema
Why it's wrong here
Single wide tables cause many NULLs and management overhead.
✓
Denormalize dimension attributes into fact tables to reduce joins
Why this is correct
Denormalization is a common BI optimization.
Clue confirmation
The clue word "best" in the question point toward this answer.
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 denormalization is always bad, but in BigQuery for BI, denormalizing dimension attributes into fact tables is a recognized best practice to reduce JOIN overhead and improve query performance.
Detailed technical explanation
How to think about this question
BigQuery partitions tables using a pseudo-column (_PARTITIONTIME) or a specified DATE/TIMESTAMP column, and each partition is stored as a separate set of columnar files in Colossus. When a query includes a filter on the partition column, BigQuery's query planner uses the table's partition metadata to skip entire partitions, a process known as partition pruning, which can reduce data scanned by orders of magnitude. Denormalizing dimension attributes into fact tables (Option E) reduces the need for JOINs, which is especially beneficial in BigQuery because JOINs can be expensive in a distributed, shared-nothing architecture; this trade-off is common in BI schemas to optimize for read-heavy analytical queries.
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.
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..
What is the correct answer to this question?
The correct answer is: Partition tables on a column that aligns with common filter criteria — Partitioning tables on a column that aligns with common filter criteria (e.g., a date or timestamp column) allows BigQuery to prune partitions during query execution, drastically reducing the amount of data scanned and improving query performance and cost efficiency. This is a core best practice for optimizing BI workloads in BigQuery.
What should I do if I get this PCDE question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Are there clue words in this question I should notice?
Yes — watch for: "best". Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
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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