Quick Answer
The answer is to use the Split Column by Delimiter transformation in Power Query. This is correct because the transformation is specifically engineered to parse a single text column into multiple columns by identifying a consistent separator, such as a space, which directly addresses the need to separate 'John Doe' into distinct 'FirstName' and 'LastName' fields. On the Microsoft Power BI Data Analyst PL-300 exam, this task tests your ability to perform data shaping and cleansing within the Power Query Editor, a core skill for preparing data for analysis. A common trap is attempting to use the Extract or Replace Values functions, which do not split a column into multiple parts; instead, they modify the existing text. To remember this, think of the delimiter as a knife that cleanly cuts the data at every space or comma, creating new columns from the pieces.
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 have a dataset with a column 'FullName' containing values like 'John Doe'. You need to split this column into 'FirstName' and 'LastName' using the space delimiter. Which Power Query transformation should you use?
Split Column by Delimiter.
Splits a column into multiple columns based on a delimiter.
Merge Columns.
Why wrong: Merge combines columns, not splits.
Extract Text.
Why wrong: Extract is for extracting characters from the beginning or end.
Replace Values.
Why wrong: Replace Values substitutes text, not splits.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Split Column by Delimiter.
Option A is correct because the 'Split Column by Delimiter' transformation in Power Query is specifically designed to divide a single text column into multiple columns based on a specified delimiter, such as a space. In this scenario, selecting the column 'FullName' and using 'Split Column > By Delimiter' with a space delimiter will correctly separate 'John Doe' into 'FirstName' (John) and 'LastName' (Doe). This is the standard approach for parsing delimited text within Power Query.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Split Column by Delimiter.
Why this is correct
Splits a column into multiple columns based on a delimiter.
Related concept
Read the scenario before looking for a memorised answer.
Merge Columns.
Why it's wrong here
Merge combines columns, not splits.
Extract Text.
Why it's wrong here
Extract is for extracting characters from the beginning or end.
Replace Values.
Why it's wrong here
Replace Values substitutes text, not splits.
Common exam traps
The trap here is that candidates may confuse 'Extract Text' with splitting, thinking it can parse delimiters, but 'Extract Text' only extracts fixed-length or positional substrings, not delimiter-based splits.
Detailed technical explanation
Under the hood, the 'Split Column by Delimiter' transformation uses the M function `Table.SplitColumn` with a `Splitter.SplitTextByDelimiter` argument, which can handle multiple delimiters and advanced options like splitting at each occurrence or only the leftmost/rightmost delimiter. A subtle behavior is that if a name contains multiple spaces (e.g., 'John Michael Doe'), the default split at each delimiter will create three columns; you can choose 'Split at the rightmost delimiter' to isolate the last name correctly. In real-world scenarios, this is critical for cleaning HR or CRM data where names may have inconsistent spacing or middle names.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
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
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FAQ
Prepare the data — This question tests Prepare the data — Read the scenario before looking for a memorised answer..
The correct answer is: Split Column by Delimiter. — Option A is correct because the 'Split Column by Delimiter' transformation in Power Query is specifically designed to divide a single text column into multiple columns based on a specified delimiter, such as a space. In this scenario, selecting the column 'FullName' and using 'Split Column > By Delimiter' with a space delimiter will correctly separate 'John Doe' into 'FirstName' (John) and 'LastName' (Doe). This is the standard approach for parsing delimited text within Power Query.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Same concept, more angles
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 using Power Query to transform a column 'FullName' containing values like 'Smith, John'. You need to split this into 'LastName' and 'FirstName' columns. Which THREE steps are required?
mediumWhy B: Options A, B, and D are correct. Split Column by delimiter (A) with comma, then you might need to trim spaces (B) and rename columns (D). Option C is wrong because unpivot is not needed. Option E is wrong because merging is the opposite of splitting.
Variation 2. You are preparing data for a Power BI report. The source data contains a column 'FullName' with values like 'John Doe'. You need to split this column into 'FirstName' and 'LastName' using Power Query. The transformation should be repeatable and not dependent on the number of spaces. What is the best approach?
mediumWhy B: Option B is correct. Splitting by delimiter (space) at the rightmost occurrence reliably separates last name from first name. Option A is wrong because splitting by position is not reliable. Option C is wrong because Extract after delimiter picks the wrong part. Option D is wrong because Replace values doesn't split.
Last reviewed: Jun 24, 2026
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.
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