PL-300 Prepare the data Practice Question
You are preparing data from a CSV file that contains date values in the format 'MM/dd/yyyy'. When you load the file into Power BI Desktop, the dates appear as text. What should you do to ensure the dates are recognized as date data type?
⚠ Common exam trap
Test-takers frequently think replacing delimiters or splitting columns will magically change the data type, but Power BI requires an explicit data type change in Power Query Editor to convert text to dates.
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
✓
Change the column data type to Date in Power Query Editor
Changing the column data type to Date in Power Query Editor forces Power BI to interpret the text values as dates using the current locale settings. Since the CSV file contains dates in 'MM/dd/yyyy' format, Power Query can parse this pattern when the data type is explicitly set to Date, converting the text strings into the Date data type for proper time intelligence and filtering.
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 'Replace Values' to replace '/' with '-'
Why it's wrong here
While replacing '/' with '-' might make the string look more like a date format (e.g., 12-31-2024), the column remains text type. Power Query does not automatically infer data types based on string manipulation; the column still contains textual values, and no date semantics are applied. To actually convert to a date, you must explicitly change the column data type in the Transform tab, which parses the string into a date based on locale and format. This action is a text transformation, not a type conversion.
- ✓
Change the column data type to Date in Power Query Editor
Why this is correct
In Power Query Editor, selecting the column and setting the Data Type to Date invokes the type conversion engine, which parses each string value using the current culture's date formats. For a CSV with dates like '12/31/2024', this transformation changes the column's metadata to DateTime/Date type, enabling date-specific transformations, filtering, and accurate loading into Power BI. Since the column is currently text, this is the necessary step to ensure Power BI treats the values as actual dates for time intelligence calculations.
- ✗
Split the column by delimiter '/'
Why it's wrong here
Splitting on the '/' delimiter divides each string into separate columns (e.g., month, day, year), but these new columns remain text. You would then have to individually convert each part to numbers, and then combine them into a date using Date.FromText or a construct, which is a circuitous and error-prone approach. It does not recognize the original column as a date structure; it deconstructs it, losing the original date format semantics.
- ✗
Promote the first row as headers
Why it's wrong here
Promoting the first row as headers simply uses that row's values as the column names; it does not alter the underlying data type of any column. The date column remains text, and the first row that might have contained date strings becomes the column header, potentially still a text label. This operation is for structuring the table schema, not for data type conversion.
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