The answer is that the column contains NULL values, which are not counted by COUNT(column). This happens because COUNT(column) ignores NULLs in the specified column, counting only non-null entries, while COUNT(*) counts every row in the result set regardless of NULLs. If even a single row has a NULL in that column, the two counts will differ. On the Google Professional Cloud Database Engineer exam, this tests your understanding of fundamental SQL aggregation behavior and how it affects BI query accuracy—a common trap is assuming COUNT(column) and COUNT(*) are interchangeable. Remember the memory tip: COUNT(*) counts the stars in the sky (every row), while COUNT(column) counts only the stars that shine (non-null values).
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.
A BI query uses COUNT(column) to count non-null values and COUNT(*) to count all rows. The analyst expects both counts to be equal, but COUNT(column) returns fewer rows. What is the most likely explanation?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "most likely"
Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The column contains NULL values, which are not counted by COUNT(column).
COUNT(column) ignores NULL values in the specified column, while COUNT(*) counts every row in the result set regardless of NULLs. If the column contains any NULLs, COUNT(column) will return a lower number. This is a fundamental SQL behavior defined in the ANSI SQL standard and is consistent across all major BI platforms (e.g., Tableau, Power BI, Looker) that generate SQL queries.
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.
✗
The query has a WHERE clause that filters some rows.
Why it's wrong here
A WHERE clause would affect both counts equally.
✗
COUNT(*) is faster, so it's not accurate.
Why it's wrong here
Both are accurate.
✗
COUNT(*) counts duplicate rows, while COUNT(column) does not.
Why it's wrong here
COUNT(*) includes duplicates; COUNT(column) also includes duplicates.
✓
The column contains NULL values, which are not counted by COUNT(column).
Why this is correct
COUNT(column) only counts non-null values.
Clue confirmation
The clue word "most likely" 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 subtle distinction between COUNT(*) and COUNT(column) by embedding NULL values in the column, tempting candidates to incorrectly attribute the difference to duplicates or filtering.
Detailed technical explanation
How to think about this question
Under the hood, COUNT(*) operates on the entire row, incrementing for every row in the result set, while COUNT(column) evaluates each row's column value and increments only if the value is not NULL. In BI tools like Tableau, when you drag a measure to the view, the underlying SQL often uses COUNT(column) on a specific field, and if that field has NULLs (e.g., due to left joins or sparse data), the count will be lower than the row count. A real-world scenario is counting orders versus counting customers in a left-joined table where some orders have no customer ID.
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 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
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: The column contains NULL values, which are not counted by COUNT(column). — COUNT(column) ignores NULL values in the specified column, while COUNT(*) counts every row in the result set regardless of NULLs. If the column contains any NULLs, COUNT(column) will return a lower number. This is a fundamental SQL behavior defined in the ANSI SQL standard and is consistent across all major BI platforms (e.g., Tableau, Power BI, Looker) that generate SQL queries.
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: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
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.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.