Microsoft Certification, PL-300, Power BI

Practice Questions: Resolve Data Import Errors (PL-300 Exam Prep)

 
This post is a part of the PL-300: Microsoft Power BI Data Analyst Exam Prep Hub; and this topic falls under these sections:
Prepare the data (25–30%)
   --> Profile and clean the data
      --> Resolve Data Import Errors

Below are 10 practice questions (with answers and explanations) for this topic of the exam.
There are also 2 practice tests for the PL-300 exam with 60 questions each (with answers) available on the hub.

Practice Questions

1. Identifying the Cause of an Import Error

A column fails to load because Power BI cannot convert certain values to a numeric data type. What is the MOST likely cause?

A. Duplicate values in the column
B. Text values mixed with numeric values
C. The column contains too many rows
D. The column is hidden

Correct Answer: B

Explanation:
Type conversion errors commonly occur when text values (such as "N/A" or "Unknown") exist in a column expected to be numeric.

2. Viewing Only Error Rows

You want to see only the rows that caused an import error in Power Query. What should you do?

A. Enable Column distribution
B. Use Keep Errors on the column
C. Change the column data type
D. Open Advanced Editor

Correct Answer: B

Explanation:
Keep Errors filters the column to show only rows containing error values, making troubleshooting easier.

3. Best First Step When Errors Occur

A column shows error values after changing its data type. What is the BEST initial action?

A. Remove all error rows
B. Replace errors with null
C. Identify and fix the source values
D. Disable query refresh

Correct Answer: C

Explanation:
Best practice is to fix the root cause (invalid source values) before applying type conversion or replacing errors.

4. Handling Errors Without Losing Rows

You want to keep all rows but avoid breaking visuals caused by error values. What should you do?

A. Remove rows with errors
B. Replace errors with null
C. Replace values with zero
D. Delete the column

Correct Answer: B

Explanation:
Replacing errors with null preserves rows while preventing calculation and visualization failures.

5. Import Errors After Removing a Column

A query fails after a column is removed earlier in the applied steps. What is the MOST likely reason?

A. The column had duplicate values
B. A later step references the removed column
C. The column contained nulls
D. The column data type was incorrect

Correct Answer: B

Explanation:
Applied steps are sequential. If a later step references a removed or renamed column, the query will fail.

6. Merge Query Errors

A merge query fails because matching columns have different data types. What should you do?

A. Replace errors with null
B. Change both columns to the same data type
C. Remove duplicate rows
D. Use a conditional column

Correct Answer: B

Explanation:
Merge keys must have matching data types. Mismatches commonly cause merge errors.

7. Fixing Date Conversion Errors

Dates import as text and generate errors when converted to Date. The issue is caused by regional formatting differences. What is the BEST solution?

A. Replace errors with today’s date
B. Remove the column
C. Change data type using locale
D. Fill down the column

Correct Answer: C

Explanation:
Using Locale allows Power BI to correctly interpret date formats based on regional settings.

8. Understanding Replace Errors

What does the Replace Errors transformation do?

A. Removes rows with errors
B. Replaces null values only
C. Substitutes error values with a specified value
D. Fixes the underlying data issue automatically

Correct Answer: C

Explanation:
Replace Errors allows you to replace error values with a defined value (often null), but it does not fix the root cause.

9. Diagnosing Transformation Errors

Which Power Query feature helps identify which step in the query caused an error?

A. Column quality
B. Query dependencies
C. Applied Steps pane
D. Data view

Correct Answer: C

Explanation:
The Applied Steps pane shows each transformation and highlights where errors occur.

10. Best Practice for Preventing Import Errors

Which approach BEST reduces the risk of data import errors?

A. Converting data types as early as possible
B. Cleaning and validating data before type conversion
C. Removing all null values
D. Importing fewer columns

Correct Answer: B

Explanation:
Cleaning data before assigning data types prevents conversion errors and ensures stable transformations.

✅ PL-300 Exam Takeaways

  • Import errors usually stem from type mismatches, invalid values, or broken applied steps
  • Fixing the root cause is preferred over removing data
  • Know when to use Replace Errors, Keep Errors, and Remove Errors
  • Expect scenario-based questions that test transformation order and reasoning

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