DP-203 Develop data processing Practice Question
You are designing an ETL process in Azure Data Factory. You need to transform data using Mapping Data Flows. Which THREE of the following transformations are available in Mapping Data Flows?
⚠ Common exam trap
Test-takers frequently confuse the 'Union All' and 'Merge Join' names from other tools (like SSIS or T-SQL) with the actual transformation names in Azure Data Factory Mapping Data Flows, leading them to select options that sound familiar but are not available.
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
✓
Pivot
The Pivot transformation in Mapping Data Flows allows you to rotate data from rows into columns, enabling aggregation and restructuring of datasets. It is a native transformation in Azure Data Factory's Mapping Data Flows, supporting group-by columns, pivot keys, and aggregated column values.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Pivot
Why this is correct
Used to rotate data from rows to columns.
- ✓
Derived Column
Why this is correct
Creates new columns based on expressions.
- ✗
Union All
Why it's wrong here
Union is the correct transformation; Union All is not a distinct transformation.
- ✓
Aggregate
Why this is correct
Used for grouping and aggregations.
- ✗
Merge Join
Why it's wrong here
The transformation is called 'Join', not 'Merge Join'.
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