The answer is to replace the comma with an empty string in Power Query Editor, then change the data type to Decimal Number. This approach is correct because it cleans the text-based numeric data directly in the M language transformation layer, which is far more efficient and scalable than using DAX calculated columns in the data model. When you convert text with commas to number in Power Query, you remove the thousands separator that prevents automatic type detection, allowing Power Query to interpret the value as a true decimal. On the PL-300 exam, this scenario tests your understanding of data preparation best practices, often appearing as a distractor where candidates might incorrectly choose to handle the conversion via DAX or by changing the locale settings. A common trap is assuming Power BI will automatically parse regional number formats, but Power Query requires explicit steps. Memory tip: think “strip the comma, then decimal” — always clean text before changing the data type.
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 Power BI report. The source data contains a column with values like '1,234.56' formatted as text. You need to convert this to a numeric value for calculations. What is the best approach?
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
✓
In Power Query Editor, replace the comma with an empty string, then change the data type to Decimal Number.
Option C is correct because Power Query Editor provides the most efficient and scalable method for cleaning and converting text-based numeric data. By replacing the comma with an empty string and then changing the column data type to Decimal Number, you perform the transformation directly in the data preparation layer (M language), which is optimized for performance and avoids the overhead of DAX calculated columns. This approach also ensures the data remains clean for all downstream calculations.
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.
✗
In Power Query Editor, split the column by comma and then use the second part.
Why it's wrong here
Splitting loses the integer part.
✗
In DAX, create a calculated column using VALUE() after removing commas.
Why it's wrong here
Better to clean data in Power Query before loading.
✓
In Power Query Editor, replace the comma with an empty string, then change the data type to Decimal Number.
Why this is correct
This removes the formatting and converts to number.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
In Power Query Editor, use the 'Clean' transform to remove non-numeric characters.
Why it's wrong here
Clean removes non-printable characters, not commas.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Microsoft often tests the misconception that the 'Clean' transform removes all non-numeric characters, but in reality it only removes non-printable control characters, not punctuation like commas or periods.
Detailed technical explanation
How to think about this question
Under the hood, Power Query uses the M language's Table.TransformColumns function with Text.Replace to remove commas, and then Type.TransformColumnType to convert the cleaned text to a Decimal.Type. This transformation is applied during data load, meaning the data is stored as a numeric type in the Power BI data model, enabling efficient aggregations and relationships. A subtle behavior to note: if the source data uses a comma as a decimal separator (e.g., European locale), replacing the comma would destroy the decimal precision, so you must first check the locale settings or use the 'Replace Values' step with locale-aware transformations.
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 Editor, replace the comma with an empty string, then change the data type to Decimal Number. — Option C is correct because Power Query Editor provides the most efficient and scalable method for cleaning and converting text-based numeric data. By replacing the comma with an empty string and then changing the column data type to Decimal Number, you perform the transformation directly in the data preparation layer (M language), which is optimized for performance and avoids the overhead of DAX calculated columns. This approach also ensures the data remains clean for all downstream calculations.
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.
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.
About these practice questions
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These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. You are transforming data in Power Query. A column named 'SalesAmount' contains values as text with a dollar sign and thousands separator, e.g., "$1,234.56". You need to convert this column to a decimal number for analysis. What is the most efficient sequence of transformations?
easy
A.Split the column by delimiter and keep the numeric part, then change data type.
B.Change data type to Decimal Number directly; Power Query will automatically clean the values.
✓ C.Use Replace Values to remove '$' and ',', then change data type to Decimal Number.
D.Use Replace Values to remove '$' and ',' then change data type to Decimal.
Why C: Option C is correct because it explicitly removes both the dollar sign and the comma before changing the data type, ensuring that Power Query can interpret the cleaned text as a decimal number without errors. Directly changing the data type (Option B) would fail because Power Query cannot automatically parse currency symbols and thousands separators from text. Option A is inefficient because splitting the column is unnecessary when simple replacements suffice. Option D is identical to C but omits the comma removal, which would leave the thousands separator and cause conversion failures.
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This PL-300 practice question is part of Courseiva's free Microsoft 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 PL-300 exam.
Question Discussion
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