PL-300 Prepare the data Practice Question
You have a table with a column 'FullName' that contains names in the format 'Last, First'. You need to split this column into 'LastName' and 'FirstName' columns. Which Power Query transformation should you use?
⚠ Common exam trap
The trap here is that candidates might confuse 'Split Column by Delimiter' with 'Extract' or 'Pivot', thinking that extracting the first few characters or pivoting the column could achieve the same result, but only the delimiter-based split correctly handles the variable-length 'Last, First' format.
Answer choices
Why each option matters
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 using comma.
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 comma. In this case, the 'FullName' column contains names in the 'Last, First' format, so splitting by a comma delimiter will correctly separate the last name and first name into two distinct columns.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Pivot the FullName column.
Why it's wrong here
Pivot is an aggregation-based transformation that turns unique values in a column into new columns, typically with an aggregate value. It does not parse or split the contents of a cell. Using Pivot on FullName would create a wide table with one column per unique name, not separate first and last name fields.
- ✓
Split Column by Delimiter using comma.
Why this is correct
In Power Query, the Split Column feature by a delimiter divides text into separate columns at each occurrence of a specified delimiter. For a FullName column containing comma-separated names, choosing comma as the delimiter splits it into two columns, with options to control the number of splits and how to handle extra delimiters. This directly achieves the goal of separating the name into distinct parts.
- ✗
Group By the FullName column and aggregate.
Why it's wrong here
Group By is an aggregation operation that groups rows sharing a common value in a column and computes summary statistics like counts, sums, or averages. It operates on the row level, not on the text content within each cell, so it cannot separate a full name into its components. Grouping by FullName would just return distinct names with aggregated measures, which is not what the goal requires.
- ✗
Extract first characters using 'Extract' transformation.
Why it's wrong here
The Extract transformation in Power Query, such as Extract First Characters or Extract Text Before Delimiter, copies a substring from the existing value into a new column but does not split the original value into multiple independent columns. For instance, extracting first characters would only retrieve a prefix like the first letter, which does not separate the full name into first and last names. It is not a splitting operation and would not accomplish the task.
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