PL-300 Null handling in Power Query Practice Question
You are preparing data for a Power BI report. You have a table that contains a 'ProductID' column with some null values. You need to ensure that the 'ProductID' column does not contain any null values in the data model. Which Power Query transformation should you apply?
⚠ Common exam trap
The trap is thinking that 'Remove Blank Rows' removes rows with any null in a column; actually it only removes rows where every cell in the row is null. For a specific column like ProductID, filtering rows where ProductID is null or replacing nulls are the correct approaches.
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
✓
Replace Values -> Replace null with a default value
Replacing null values with a default value directly ensures that the ProductID column has no nulls in the data model. This transformation can be applied to a specific column using 'Replace Values' in Power Query, where you replace null with a chosen default. Options A and B do not address null values. Option C, 'Remove Blank Rows', only removes rows where all columns are blank, so rows with data in other columns but null ProductID remain, failing the requirement.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Group By
Why it's wrong here
Group By is an aggregation operation that groups rows based on selected columns and computes summary statistics like counts or sums. It does not edit cell-level values, so nulls in ProductID would remain null within each group. Moreover, grouping might combine rows with null ProductID into a separate bucket, but it does not transform those nulls into meaningful identifiers, so it fails to meet the data preparation goal.
- ✗
Remove Duplicates
Why it's wrong here
Remove Duplicates is designed to eliminate repeated rows that share identical values across selected columns, but it has no mechanism for resolving null entries. If multiple rows contain the same non-null ProductID, deduplication might delete some rows, yet any row with a null ProductID stays unchanged. Since the objective is to ensure every ProductID is populated, this command is functionally irrelevant to null-value handling.
- ✗
Remove Rows -> Remove Blank Rows
Why it's wrong here
Remove Rows -> Remove Blank Rows only eliminates rows where every column in the row is null. In your scenario, ProductID may be null while other columns contain values, so those rows will remain intact with the null ProductID still present. This operation discards entire records rather than repairing missing identifiers, and thus fails to satisfy the requirement of having no nulls in the ProductID column.
- ✓
Replace Values -> Replace null with a default value
Why this is correct
Replace Values -> Replace null with a default value is the correct approach because it directly modifies the ProductID column, converting each null into a specified default such as 'Unknown' or '0'. This preserves all rows while guaranteeing that no empty ProductID values remain, which is exactly the requirement. Power Query's Replace Values operation supports replacing nulls specifically, making it a targeted and effective data-cleaning step.
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