The correct answer is to remove duplicates from the CustomerID column in the CSV table before merging in Power Query. This ensures a clean one-to-one or one-to-many relationship with the SQL sales data, preventing inflated row counts and inaccurate aggregations that would occur if duplicate customer IDs were left in the demographic table. On the Microsoft Power BI Data Analyst PL-300 exam, this scenario tests your understanding of data preparation and referential integrity, often appearing as a trap where candidates mistakenly merge first and clean later, leading to mismatched cardinality. The key is to handle duplicate customer IDs before merging Power Query tables, as the Remove Duplicates operation keeps the first occurrence by default, which is sufficient when no other filtering criteria are specified. Memory tip: think “clean before you join” to avoid a messy model.
PL-300 Prepare the data Practice Question
This PL-300 practice question tests your understanding of prepare the data. 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.
You are preparing data for a report that requires joining sales data from a SQL database with customer demographic data from a CSV file. The CSV file contains duplicate customer IDs. How should you handle duplicates to ensure accurate analysis?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
In Power Query, remove duplicates from the CustomerID column in the CSV table before merging.
Option D is correct because removing duplicates from the CustomerID column in the CSV table before merging ensures a one-to-one or one-to-many relationship with the SQL sales data, preventing inflated row counts and inaccurate aggregations. In Power Query, the 'Remove Duplicates' operation keeps the first occurrence by default, which is appropriate when no other filtering criteria are specified. This step is critical for maintaining referential integrity in the data model.
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.
✗
Group by CustomerID and aggregate all columns.
Why it's wrong here
Aggregating all columns may lose important details.
✗
In Power Query, use 'Merge Queries' and select 'Merge with duplicates' option.
Why it's wrong here
Merge with duplicates does not exist; you need to remove duplicates first.
✗
Load both tables as-is and create a relationship in the data model.
Why it's wrong here
Duplicates will cause a many-to-many relationship, which can lead to incorrect aggregations.
✓
In Power Query, remove duplicates from the CustomerID column in the CSV table before merging.
Why this is correct
Removing duplicates ensures a clean dimension table.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Microsoft often tests the misconception that Power Query can automatically handle duplicates during a merge operation, but in reality, you must explicitly remove or deduplicate the key column before merging to avoid data inflation.
Detailed technical explanation
How to think about this question
Under the hood, Power Query's 'Remove Duplicates' uses the Table.Distinct function, which compares rows based on the selected columns and retains the first occurrence. In a real-world scenario, if the CSV contains duplicate CustomerIDs with conflicting demographic data (e.g., different cities), you might need to apply business logic (e.g., keep the most recent record) before removing duplicates, rather than blindly keeping the first row. This nuance is often tested in PL-300 to ensure candidates understand data cleansing trade-offs.
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.
Prepare the data — This question tests Prepare the data — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: In Power Query, remove duplicates from the CustomerID column in the CSV table before merging. — Option D is correct because removing duplicates from the CustomerID column in the CSV table before merging ensures a one-to-one or one-to-many relationship with the SQL sales data, preventing inflated row counts and inaccurate aggregations. In Power Query, the 'Remove Duplicates' operation keeps the first occurrence by default, which is appropriate when no other filtering criteria are specified. This step is critical for maintaining referential integrity in the data model.
What should I do if I get this PL-300 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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Question Discussion
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