- A
SELECT EXTRACT(MONTH FROM created_date) AS month, COUNT(*) FROM shipments WHERE TIMESTAMP_DIFF(delivery_date, created_date, HOUR) <= 120 AND EXTRACT(YEAR FROM created_date) = 2024 GROUP BY month
Why wrong: TIMESTAMP_DIFF in hours is less readable and may have timezone issues.
- B
SELECT EXTRACT(MONTH FROM created_date) AS month, COUNTIF(DATETIME_DIFF(delivery_date, created_date, DAY) <= 5) FROM shipments WHERE EXTRACT(YEAR FROM created_date) = 2024 GROUP BY month
Why wrong: COUNTIF works but filtering in WHERE is more efficient.
- C
SELECT EXTRACT(MONTH FROM created_date) AS month, COUNT(*) FROM shipments WHERE DATETIME_DIFF(delivery_date, created_date, DAY) <= 5 AND EXTRACT(YEAR FROM created_date) = 2024 GROUP BY month
Correct function and clear intent.
- D
SELECT EXTRACT(MONTH FROM created_date) AS month, COUNT(*) FROM shipments WHERE DATE_DIFF(delivery_date, created_date, DAY) <= 5 AND EXTRACT(YEAR FROM created_date) = 2024 GROUP BY month
Why wrong: DATE_DIFF expects DATE type, but columns are likely TIMESTAMP.
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. Compare every option against the stated constraints before choosing — the best answer satisfies all requirements, not just the most obvious one. 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 logistics company uses BigQuery to track shipments. The `shipments` table has columns `id`, `status`, `created_date`, and `delivery_date`. They need a query that returns the number of shipments that were delivered within 5 days of creation for each month of 2024. Which SQL construct is most appropriate?
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
SELECT EXTRACT(MONTH FROM created_date) AS month, COUNT(*) FROM shipments WHERE DATETIME_DIFF(delivery_date, created_date, DAY) <= 5 AND EXTRACT(YEAR FROM created_date) = 2024 GROUP BY month
Option C is correct because it uses `DATETIME_DIFF` with `DAY` precision to accurately compute the difference between `delivery_date` and `created_date` in days, and filters for shipments delivered within 5 days (i.e., <= 5 days). The `WHERE` clause also restricts to the year 2024, and the `GROUP BY month` with `EXTRACT(MONTH FROM created_date)` correctly aggregates counts per month. This matches the requirement precisely.
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.
- ✗
SELECT EXTRACT(MONTH FROM created_date) AS month, COUNT(*) FROM shipments WHERE TIMESTAMP_DIFF(delivery_date, created_date, HOUR) <= 120 AND EXTRACT(YEAR FROM created_date) = 2024 GROUP BY month
Why it's wrong here
TIMESTAMP_DIFF in hours is less readable and may have timezone issues.
- ✗
SELECT EXTRACT(MONTH FROM created_date) AS month, COUNTIF(DATETIME_DIFF(delivery_date, created_date, DAY) <= 5) FROM shipments WHERE EXTRACT(YEAR FROM created_date) = 2024 GROUP BY month
Why it's wrong here
COUNTIF works but filtering in WHERE is more efficient.
- ✓
SELECT EXTRACT(MONTH FROM created_date) AS month, COUNT(*) FROM shipments WHERE DATETIME_DIFF(delivery_date, created_date, DAY) <= 5 AND EXTRACT(YEAR FROM created_date) = 2024 GROUP BY month
Why this is correct
Correct function and clear intent.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
SELECT EXTRACT(MONTH FROM created_date) AS month, COUNT(*) FROM shipments WHERE DATE_DIFF(delivery_date, created_date, DAY) <= 5 AND EXTRACT(YEAR FROM created_date) = 2024 GROUP BY month
Why it's wrong here
DATE_DIFF expects DATE type, but columns are likely TIMESTAMP.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the distinction between `DATE_DIFF`, `DATETIME_DIFF`, and `TIMESTAMP_DIFF`, and candidates mistakenly choose `DATE_DIFF` without considering the actual data types of the columns, or they use `TIMESTAMP_DIFF` with hours thinking it is equivalent, but fail to account for timezone and daylight saving effects.
Detailed technical explanation
How to think about this question
In BigQuery, `DATETIME_DIFF` is the correct function for computing the difference between two `DATETIME` values in a specified date part (e.g., DAY), and it handles time components correctly without truncation. Using `TIMESTAMP_DIFF` with hours introduces sensitivity to timezone offsets and daylight saving transitions, which can cause off-by-one errors in day boundaries. The `EXTRACT` function is used to isolate the month from a date or datetime column, and `GROUP BY` with an alias (month) is supported in BigQuery, making the query concise and efficient.
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
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
Questions learners often ask
What does this PCDE question test?
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: SELECT EXTRACT(MONTH FROM created_date) AS month, COUNT(*) FROM shipments WHERE DATETIME_DIFF(delivery_date, created_date, DAY) <= 5 AND EXTRACT(YEAR FROM created_date) = 2024 GROUP BY month — Option C is correct because it uses `DATETIME_DIFF` with `DAY` precision to accurately compute the difference between `delivery_date` and `created_date` in days, and filters for shipments delivered within 5 days (i.e., <= 5 days). The `WHERE` clause also restricts to the year 2024, and the `GROUP BY month` with `EXTRACT(MONTH FROM created_date)` correctly aggregates counts per month. This matches the requirement precisely.
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.
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
This PCDE 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 PCDE exam.
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