mediumMultiple Select
Which Three Actions Can You Perform in the Power Query Editor?
Which THREE actions can be performed in the Power Query Editor?
Quick Answer
The Power Query Editor exists specifically to reshape and clean data before it's loaded into a report, and the actions it supports reflect that purpose: removing columns lets you strip out fields that aren't needed for analysis, keeping the dataset focused and lighter to work with, while changing a column's data type, say converting a text field to a proper number, ensures values are stored in a form that Power BI can actually calculate, sort, and aggregate correctly. Both of these are classic transformation steps because they change the shape or type of the data itself rather than how it's displayed, which is the core distinction that defines Power Query's job: it operates upstream of the report canvas, on the data, whereas visuals, formatting, and layout choices happen downstream in the report view itself. When you see a question asking what can be done in the Power Query Editor, favor answers that describe transforming, cleaning, or reshaping the underlying data, such as removing or renaming columns, changing types, filtering rows, or merging queries, and rule out anything that describes visual formatting or report design, since those belong to a completely different stage of the Power BI workflow.
⚠ Common exam trap
Test-takers frequently confuse the Power Query Editor's data transformation role with the data modeling and DAX capabilities of Power BI Desktop, leading them to incorrectly select options like creating measures or relationships.
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 data types
In the Power Query Editor, option B (Change data types) is correct because the Transform and Add Column tabs provide data type commands (e.g., Text, Whole Number, Date) that let you convert a column's type as part of shaping the data. Option C (Merge queries) is correct because the Home tab's Merge Queries feature performs a join between two queries using a common column, similar to a SQL JOIN. Option D (Remove columns) is correct because the Home tab offers Remove Columns and Remove Other Columns to drop unneeded fields during transformation. Option A (Create measures) is not available in Power Query Editor; DAX measures are created in the Power BI report/Data view or in a Power Pivot model. Option E (Create relationships between tables) is also not done in Power Query Editor; relationships are defined in the model view (Power BI) or the Data Model (Excel Power Pivot).
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Create measures
Why it's wrong here
Measures are DAX calculations created in the report or model layer, not in Power Query, which produces columns and tables during transformation. It is tempting because Power Query can add calculated columns, and it would be the correct tool if the requirement were a row-level transformation rather than an aggregate measure.
- ✓
Change data types
Why this is correct
Power Query Editor provides a data type selector on the Transform tab and column headers, letting you convert text, numbers, dates and so on. Changing data types is a core transformation step, satisfying the question's requirement for actions performed in that editor.
- ✓
Merge queries
Why this is correct
Power Query Editor's Home tab offers Merge Queries, joining two tables on matching columns like a SQL join. This is a genuine transformation action available in the editor, satisfying the requirement to identify actions performed there.
- ✓
Remove columns
Why this is correct
Power Query Editor lets you remove selected columns via the Home tab's Remove Columns command, trimming the dataset during shaping. This is a standard transformation action, satisfying the question's requirement to identify actions performed in the editor.
- ✗
Create relationships between tables
Why it's wrong here
Relationships between tables are defined in the model view after data is loaded, not inside Power Query, which only shapes and transforms data before loading. It is tempting because Power Query can merge or append queries, and it would be correct if the requirement were combining tables during transformation rather than modelling them.
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Same concept, more angles
1 more way this is tested on PL-900
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. A data analyst needs to combine data from two Excel tables that have a common column 'ProductID'. Which Power BI tool should they use?
medium- A.Append Queries
- ✓ B.Merge Queries
- C.Pivot Column
- D.Group By
Why B: Merge Queries is the correct tool because it combines two tables by matching rows based on a common column (ProductID), similar to a SQL JOIN. This allows the analyst to bring in additional columns from one table into the other, which is exactly what is needed when data from two Excel tables must be integrated on a shared key.
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This PL-900 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-900 exam.