The answer is to create a calculated field that sums sales per transaction and then averages across distinct transaction IDs. This correction directly addresses the inflated averages caused by the star schema’s granularity, where each product in a transaction creates a separate row in the fact table; dividing by COUNT(*) counts every row, not each unique transaction, artificially lowering the average. On the CompTIA Data+ DA0-001 exam, this scenario tests your understanding of how fact table grain affects aggregate calculations—a common trap is forgetting to aggregate to the correct level before averaging. Remember the memory tip: “Count rows for totals, count distinct for averages” to avoid the over-counting pitfall when working with transactional star schemas.
DA0-001 Communicating Data Insights Practice Question
This DA0-001 practice question tests your understanding of communicating data insights. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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 data analyst at a retail company is building a dashboard for store managers to track sales performance. The data comes from three sources: point-of-sale (POS) systems, inventory, and customer loyalty. The POS table contains columns transaction_id, store_id, date, product_id, quantity, and price. The inventory table has product_id, store_id, stock_level, and reorder_point. The loyalty table has customer_id, transaction_id, and points_earned. The analyst creates a star schema with a sales_fact fact table containing all rows from POS, dimension tables for store, product, date, and customer. To calculate average transaction value, the analyst uses the formula SUM(quantity * price) / COUNT(*). Store managers report that the average transaction value appears too low, especially for stores with multiple registers. The analyst realizes that because each product sold in a transaction creates a separate row in sales_fact, a single transaction with multiple items contributes multiple rows. The current calculation divides by the number of rows rather than the number of distinct transactions. Which of the following is the best course of action to correct the average transaction value metric? (Choose one.)
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
✓
Create a calculated field that sums sales per transaction (quantity * price) and then averages across distinct transaction IDs
Option A is correct because it calculates total sales per transaction (summing product-level rows) and then averages across distinct transactions, fixing the over-counting issue. Option B is too vague and does not specify how to aggregate. Option C is not required since the star schema is appropriate. Option D uses median, which does not address the counting issue.
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.
✗
Use the MEDIAN function instead of AVG
Why it's wrong here
Median does not solve the counting issue; it uses the same denominator problem.
✗
Aggregate the data at the transaction level before calculating the average
Why it's wrong here
This is too vague; it does not specify how to aggregate or handle the calculation.
✗
Use a different data model that denormalizes transaction totals into a new fact table
Why it's wrong here
Unnecessarily complex; the star schema can be used with correct calculations.
✓
Create a calculated field that sums sales per transaction (quantity * price) and then averages across distinct transaction IDs
Why this is correct
This correctly computes average transaction value by first summing per transaction.
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
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
Use explanations to understand the rule behind the answer.
TExam Day Tips
→Underline the problem statement mentally.
→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 practitioner preparing for the DA0-001 exam encounters this exact type of scenario on the job. The correct answer here is not the most general option — it is the best answer for the specific constraint described. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Real exam questions reward reading the full scenario before eliminating options, because the constraint defines which answer fits.
What to study next
Got this wrong? Here's your next step.
Identify which DA0-001 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Communicating Data Insights — This question tests Communicating Data Insights — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Create a calculated field that sums sales per transaction (quantity * price) and then averages across distinct transaction IDs — Option A is correct because it calculates total sales per transaction (summing product-level rows) and then averages across distinct transactions, fixing the over-counting issue. Option B is too vague and does not specify how to aggregate. Option C is not required since the star schema is appropriate. Option D uses median, which does not address the counting issue.
What should I do if I get this DA0-001 question wrong?
Identify which DA0-001 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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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