This DP-203 practice question tests your understanding of develop data processing. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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.
You are developing a data processing pipeline in Azure Data Factory. The pipeline uses a mapping data flow to transform data. You need to ensure that the data flow can handle schema drift from the source. Which THREE of the following actions should you take? (Select THREE.)
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 settings.
Option B is correct because enabling 'Allow schema drift' in the source settings of a mapping data flow tells Azure Data Factory to accept incoming columns that are not defined in the source schema. This is essential for handling schema drift, as it prevents the pipeline from failing when new columns appear in the source data.
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.
✗
Use a 'Select' transformation to explicitly choose only the known columns.
Why it's wrong here
This would drop drifted columns.
✓
Enable 'Allow schema drift' in the source settings.
Why this is correct
This allows the data flow to accept additional columns.
Related concept
Read the scenario before looking for a memorised answer.
✓
Set 'Ignore drift column types' in the sink settings to avoid type mismatch errors.
Why this is correct
This prevents failures when drifted columns have different data types.
Related concept
Read the scenario before looking for a memorised answer.
✓
Use 'Column pattern' transformations to apply transformations to drifted columns.
Why this is correct
Column patterns allow dynamic handling of unknown columns.
Related concept
Read the scenario before looking for a memorised answer.
✗
Add a 'Derived Column' transformation for every possible column that might be added.
Why it's wrong here
This is not scalable and does not handle unknown columns.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often think they must explicitly define every column or use static transformations to handle schema drift, when in fact Azure Data Factory's mapping data flow provides dynamic mechanisms like 'Allow schema drift', column patterns, and drift type handling to automatically accommodate unknown columns.
Detailed technical explanation
How to think about this question
When 'Allow schema drift' is enabled in the source, Azure Data Factory automatically reads all columns from the source, including those not present in the dataset schema. Column patterns then allow you to apply transformations (e.g., string trimming, type casting) to any drifted column by matching on name or type patterns, without needing to know the column names in advance. In the sink, setting 'Ignore drift column types' prevents type mismatch errors by automatically converting drifted column types to the sink's expected types, ensuring the pipeline completes even if the data types of new columns differ.
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.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this DP-203 question in full detail.
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 settings. — Option B is correct because enabling 'Allow schema drift' in the source settings of a mapping data flow tells Azure Data Factory to accept incoming columns that are not defined in the source schema. This is essential for handling schema drift, as it prevents the pipeline from failing when new columns appear in the source data.
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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Question Discussion
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