- A
Enable 'Allow schema drift' in the source transformation
Allows columns to be added without breaking the pipeline.
- B
Use derived column transformation to handle each new column manually
Why wrong: Manual approach does not scale for drift.
- C
Use column pattern matching to automatically map columns with similar names
Patterns like 'col_*' can map dynamic columns.
- D
Use assertion rules to reject rows with unknown columns
Why wrong: Rejection is not handling drift; it fails the pipeline.
- E
Use a fixed schema mapping to ignore unknown columns
Why wrong: Fixed mapping would cause errors on new columns.
Question 214 of 851
DP-203 Develop data processing Practice Question
This DP-203 practice question tests your understanding of develop data processing. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
Which TWO techniques can you use to handle schema drift in Azure Data Factory mapping data flows?
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
✓
Enable 'Allow schema drift' in the source transformation
Option A is correct because enabling 'Allow schema drift' in the source transformation tells Azure Data Factory (ADF) mapping data flows to dynamically accept incoming columns that are not defined in the schema at design time. This is the primary built-in mechanism for handling schema drift without manual intervention, as it automatically propagates new columns through the data flow.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Enable 'Allow schema drift' in the source transformation
Why this is correct
Allows columns to be added without breaking the pipeline.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use derived column transformation to handle each new column manually
Why it's wrong here
Manual approach does not scale for drift.
- ✓
Use column pattern matching to automatically map columns with similar names
Why this is correct
Patterns like 'col_*' can map dynamic columns.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use assertion rules to reject rows with unknown columns
Why it's wrong here
Rejection is not handling drift; it fails the pipeline.
- ✗
Use a fixed schema mapping to ignore unknown columns
Why it's wrong here
Fixed mapping would cause errors on new columns.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse 'handling schema drift' with 'ignoring or rejecting unknown columns' (options D and E), or they think manual column-by-column handling (option B) is a valid technique, when in fact ADF provides automated drift handling through the source setting and pattern matching.
Detailed technical explanation
How to think about this question
Under the hood, when 'Allow schema drift' is enabled, ADF mapping data flows use a dynamic schema model where columns are represented as a flexible set of name-value pairs. This allows downstream transformations like 'Select' or 'Sink' to use column pattern matching (e.g., matching by name or data type) to automatically map drifted columns to outputs. In real-world scenarios, such as ingesting JSON files with varying fields from an API, combining 'Allow schema drift' with column patterns in the Sink transformation ensures new fields are written to a target without breaking the pipeline.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Questions learners often ask
What does this DP-203 question test?
Develop data processing — This question tests Develop data processing — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Enable 'Allow schema drift' in the source transformation — Option A is correct because enabling 'Allow schema drift' in the source transformation tells Azure Data Factory (ADF) mapping data flows to dynamically accept incoming columns that are not defined in the schema at design time. This is the primary built-in mechanism for handling schema drift without manual intervention, as it automatically propagates new columns through the data flow.
What should I do if I get this DP-203 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
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