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 BI analyst needs to calculate a running total of sales by region over time in BigQuery. Which SQL window function should be used?
RANK() OVER (PARTITION BY region ORDER BY date)
Why wrong: RANK assigns a rank, not a sum.
SUM(sales) OVER (PARTITION BY region ORDER BY date)
This correctly computes a running total per region.
ROW_NUMBER() OVER (PARTITION BY region ORDER BY date)
Why wrong: ROW_NUMBER assigns row numbers, not sums.
COUNT(sales) OVER (PARTITION BY region ORDER BY date)
Why wrong: COUNT counts rows, not sums.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
SUM(sales) OVER (PARTITION BY region ORDER BY date)
Option B is correct because the SUM() window function with an ORDER BY clause in the OVER() clause computes a running total (cumulative sum) over the specified partition. In BigQuery, when you include ORDER BY inside a window function's OVER() clause, the default window frame is RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW, which produces the running total for each region ordered by date.
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.
RANK() OVER (PARTITION BY region ORDER BY date)
Why it's wrong here
RANK assigns a rank, not a sum.
SUM(sales) OVER (PARTITION BY region ORDER BY date)
Why this is correct
This correctly computes a running total per region.
Related concept
Read the scenario before looking for a memorised answer.
ROW_NUMBER() OVER (PARTITION BY region ORDER BY date)
Why it's wrong here
ROW_NUMBER assigns row numbers, not sums.
COUNT(sales) OVER (PARTITION BY region ORDER BY date)
Why it's wrong here
COUNT counts rows, not sums.
Common exam traps
Google Cloud often tests the distinction between aggregate functions (SUM, COUNT) and ranking functions (RANK, ROW_NUMBER) in window functions, and the trap here is that candidates confuse RANK() or ROW_NUMBER() with the ability to compute a running total, not realizing that only SUM() with an ORDER BY clause produces a cumulative sum.
Detailed technical explanation
In BigQuery, the default window frame for an ORDER BY clause is RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW, which includes all rows with the same ORDER BY value as the current row. This can cause unexpected results if there are duplicate dates, as the running total will include all rows with the same date, not just the current row. To get a strict row-by-row running total, use ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW instead.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
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: SUM(sales) OVER (PARTITION BY region ORDER BY date) — Option B is correct because the SUM() window function with an ORDER BY clause in the OVER() clause computes a running total (cumulative sum) over the specified partition. In BigQuery, when you include ORDER BY inside a window function's OVER() clause, the default window frame is RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW, which produces the running total for each region ordered by date.
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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