DP-203 Develop data processing Practice Question
You are creating an Azure Data Factory data flow that transforms data from an Azure SQL Database. The data flow must filter rows based on a column value and then aggregate the results. Which transformation should you use first?
⚠ Common exam trap
The trap here is assuming that the order of transformations doesn't matter or that aggregation should come first for performance, when actually filtering first reduces the data volume and ensures correct aggregation results.
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
✓
Filter transformation
Filtering rows before aggregation reduces the amount of data processed by the Aggregate transformation, improving performance and ensuring that only relevant rows are aggregated. The Filter transformation is designed to select rows based on a condition, making it the appropriate first step. Other transformations like Aggregate, Derived Column, or Join do not directly filter rows and would be less efficient or incorrect in this context.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Filter transformation
Why this is correct
The Filter transformation allows you to select rows based on a condition. Applying it first reduces the number of rows that subsequent transformations must process, improving performance and ensuring that aggregation only includes relevant data. In a data flow, transformations are executed in the order they are defined, so placing Filter before Aggregate is the correct sequence to meet the requirement of filtering then aggregating.
- ✗
Derived Column transformation
Why it's wrong here
The Derived Column transformation is used to create new columns or modify existing ones based on expressions. While it can be used to create a flag for filtering, it does not filter rows itself. If used first, it would add unnecessary columns before filtering, potentially increasing data volume and complexity. The scenario requires filtering based on a column value, so a Filter transformation is more direct and efficient.
- ✗
Join transformation
Why it's wrong here
The Join transformation combines data from two streams based on a condition. It is not relevant to filtering rows from a single source. Using a Join first would require another dataset and would not accomplish the filtering requirement. It would also add unnecessary complexity and potential performance overhead. Therefore, it is not the correct transformation to use first in this scenario.
- ✗
Aggregate transformation
Why it's wrong here
The Aggregate transformation is used to group and summarize data, such as calculating sums or averages. However, if you apply aggregation before filtering, you would aggregate unnecessary rows, potentially leading to incorrect results and reduced performance. Filtering should be done first to reduce the dataset before aggregation, ensuring that only relevant rows are aggregated. Therefore, using Aggregate first is not the optimal approach.
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Last reviewed September 2026 · checked against the official Microsoft exam blueprint
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