PL-300 Prepare the data Practice Question
A data analyst needs to combine two queries in Power Query: 'Sales2023' and 'Sales2024', both with identical column structures. Which operation should the analyst use to append the rows from 'Sales2024' to 'Sales2023'?
⚠ Common exam trap
It's easy for candidates to confuse Append Queries with Merge Queries, thinking both combine data, but Merge Queries joins columns horizontally (like a SQL JOIN) while Append Queries stacks rows vertically.
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
✓
Append Queries
The Append Queries operation in Power Query is designed to combine rows from two or more tables with identical column structures, stacking the rows of 'Sales2024' beneath those of 'Sales2023'. This is the correct method because it preserves all columns and adds data vertically, which matches the requirement to append rows.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Append Queries
Why this is correct
Append Queries is the correct tool because it stacks rows from two or more queries vertically, creating a single output table that contains every record from each input. In Power Query, this operation—equivalent to UNION ALL in SQL—is used when the inputs share a common column schema, such as merging January and February sales records. Appending does not alter existing rows or add columns; it simply lengthens the dataset.
- ✗
Merge Queries
Why it's wrong here
Merge Queries is incorrect here because it performs a horizontal join, combining columns from two different queries based on matching key columns, much like a SQL join. This operation enriches one table with related attributes from another and can even duplicate rows if there are multiple matches, whereas the requirement is to consolidate rows. Because the question asks to combine by stacking, not by complementing columns, merge is not the appropriate choice.
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Group By
Why it's wrong here
Group By is not a method to combine two queries—it is an aggregation transformation applied within a single query. It partitions rows into distinct groups defined by one or more columns and produces summary statistics (such as count, sum, or average) for each group, thereby reducing the number of rows. This operation loses the original row-level detail and cannot return the full dataset, which disqualifies it from combining multiple tables.
- ✗
Pivot Column
Why it's wrong here
Pivot Column is a reshaping tool that takes unique values from a selected column and turns them into new columns, typically with an aggregated or literal value in the cross-section cells. It transforms a long, narrow table into a wide format, but it operates on only one query and does not bring in records from a second query. Since the requirement is to stack rows from two queries, pivoting would not achieve the desired vertical union.
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