The answer is that the fileName property is hardcoded and not parameterized. This is the most likely cause because in Azure Data Factory, when a dataset’s fileName is set to a static value like 'sales.parquet', every pipeline run writes to that exact file, overwriting it regardless of how the folderPath parameter changes dynamically. The folderPath only controls the directory, not the file name, so without parameterizing fileName, the copy activity always targets the same file. On the Microsoft Azure Data Engineer Associate DP-203 exam, this scenario tests your understanding of dataset parameterization and the distinction between folder-level and file-level dynamic expressions. A common trap is assuming that parameterizing folderPath alone prevents overwrites, but the fileName must also be dynamic—often using expressions like @{pipeline().RunId} or @{formatDateTime(utcnow(),'yyyyMMdd')}—to generate unique output files. Memory tip: “Folders guide the path, but the file name decides the fate.”
DP-203 Design and implement data storage Practice Question
This DP-203 practice question tests your understanding of design and implement data storage. 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.
You are reviewing an Azure Data Factory dataset JSON definition for a data lake. The dataset is used in a copy activity that loads sales data into Azure Data Lake Storage Gen2. The pipeline runs successfully, but you notice that the output file always overwrites the previous file with the name 'sales.parquet' regardless of the folderPath parameter. What is the most likely cause?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "most likely"
Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
Clue: "always"
Why it matters: Absolute qualifier. An answer using 'always' is only correct if there are genuinely no exceptions — absolute statements are often wrong in networking.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The fileName property is hardcoded and not parameterized
Option C is correct because the dataset's fileName property is hardcoded to 'sales.parquet', which means every pipeline run writes to the same file, overwriting it regardless of the folderPath parameter. In Azure Data Factory, if fileName is static and not parameterized, the copy activity will always target that exact file name, even if folderPath changes dynamically.
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.
✗
The folderPath parameter is not being evaluated correctly
Why it's wrong here
The folderPath uses dynamic expressions and should work.
✗
The linkedServiceName is not correctly configured
Why it's wrong here
The linkedServiceName is present and presumably correct.
✓
The fileName property is hardcoded and not parameterized
Why this is correct
The fileName is fixed to 'sales.parquet', causing overwrites.
Clue confirmation
The clue words "most likely", "always" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
The format type is incorrect; it should be 'Parquet' instead of 'ParquetFormat'
Why it's wrong here
'ParquetFormat' is a valid format type in Data Factory.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often focus on folderPath or linked service configuration, overlooking that the fileName property is hardcoded, which is the direct cause of the overwrite behavior.
Detailed technical explanation
How to think about this question
In Azure Data Factory, datasets define the structure and location of data. When a dataset is used in a copy activity, the fileName property determines the exact file name written to the sink. If fileName is not parameterized, every pipeline run will overwrite the same file, even if folderPath is dynamic. To avoid this, you should parameterize both folderPath and fileName, or use dynamic expressions like @concat('sales_', formatDateTime(utcnow(), 'yyyyMMdd'), '.parquet') to generate unique file names per run.
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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this DP-203 question in full detail.
Design and implement data storage — This question tests Design and implement data storage — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: The fileName property is hardcoded and not parameterized — Option C is correct because the dataset's fileName property is hardcoded to 'sales.parquet', which means every pipeline run writes to the same file, overwriting it regardless of the folderPath parameter. In Azure Data Factory, if fileName is static and not parameterized, the copy activity will always target that exact file name, even if folderPath changes dynamically.
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.
Are there clue words in this question I should notice?
Yes — watch for: "most likely", "always". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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