PL-300 Prepare the data Practice Question
You are preparing data for a Power BI report. The source data contains a column with mixed data types: some values are numbers, others are text. When loading into Power Query, the entire column is typed as text. What is the likely cause?
⚠ Common exam trap
Candidates often assume the data source format (e.g., CSV) is the cause, but Power Query's type detection logic—not the source—is what forces the column to text when mixed data types are present.
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
✓
Power Query detected that the column contains text values in some rows, so it set the data type to text
Power Query's column type detection logic examines the entire column during import. If any row contains a non-numeric value (e.g., text), Power Query defaults the entire column to text to avoid data loss or conversion errors. This is the standard behavior when mixed data types are present, regardless of the source format.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The column was imported as text because the data source is a CSV file
Why it's wrong here
While CSV files are plain text and do not enforce a schema, Power Query still runs its type-detection logic on the imported values. The column being typed as text here is not an automatic consequence of the CSV format; rather, it is the outcome of Power Query's inference seeing non-numeric entries in some rows. Thus, the file format alone does not explain the text result.
- ✓
Power Query detected that the column contains text values in some rows, so it set the data type to text
Why this is correct
Power Query's automatic data type detection examines the values in each column and, when it encounters a mixture of numeric and textual entries, it deliberately selects the text data type. This ensures every value can be represented without conversion errors, because coercing text like 'N/A' into a number would fail. In this scenario, the presence of text values in some rows explains why the column was set to text.
- ✗
The 'Detect data type' option was disabled in Power Query settings
Why it's wrong here
If the 'Detect data type' option were disabled, Power Query would not infer any specific data type; instead, columns would remain as 'Any' (or the engine's raw type) until you explicitly set them. A disabled detector would not produce a text-typed column at all, so that setting cannot be the cause. The fact that the column shows as text indicates detection actually ran and made a decision based on mixed values.
- ✗
The source data is stored as text in the database
Why it's wrong here
If the source database column truly stored all data as text, Power Query would typically import it with a text data type without needing to infer a mixed result. But the question describes mixed types in the source, meaning some rows contain numbers and others contain text. The database's storage type is not the deciding factor; Power Query's type detection evaluates the actual values and falls back to text because of the mix, independent of how the database originally stored them.
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Same concept, more angles
1 more way this is tested on PL-300
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 importing data from a CSV file that contains a column with mixed data types (numbers and text). Power BI automatically assigns the data type as Text. You need to perform numerical aggregations on this column. What should you do?
easy- A.Split the column using a delimiter to separate numbers from text.
- B.Create a relationship with a numeric table to enable aggregation.
- C.Create a calculated column in DAX using VALUE() to convert the text to numbers.
- ✓ D.In Power Query Editor, change the data type of the column to Whole Number or Decimal Number.
Why D: Changing the column's data type to Whole Number or Decimal Number in Power Query Editor will force Power BI to interpret the numeric values as numbers, enabling aggregations like SUM or AVERAGE. Power Query Editor provides a robust transformation environment where data type changes are applied during the load process, ensuring the column is treated as numeric for all downstream calculations. This approach is more efficient and reliable than using DAX conversions, as it avoids the overhead of calculated columns and leverages Power Query's native type detection and error handling.
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.