- A
Azure Data Factory
Azure Data Factory is designed for orchestrating data pipelines with scheduling, monitoring, and error handling. It can copy CSV files from Azure Data Lake Storage to Azure Synapse Analytics and handle failures gracefully.
- B
Azure Stream Analytics
Why wrong: Azure Stream Analytics is for real-time stream processing, not for scheduled batch loading of files. It cannot directly load CSV files from storage into Synapse on a nightly schedule.
- C
Azure Databricks
Why wrong: Azure Databricks can process data and write to Synapse, but it is a compute engine, not a scheduling and orchestration service. It can be used within a pipeline orchestrated by Data Factory, but alone it lacks native scheduling and error-handling capabilities for simple file loads.
- D
Azure Logic Apps
Why wrong: Azure Logic Apps can automate workflows and integrate with various services, but it is better suited for smaller-scale integrations and app workflows. For heavy data movement and transformation at scale, Azure Data Factory is the correct choice.
Quick Answer
The answer is Azure Data Factory, the correct choice because it is a cloud-based ETL and data integration service built specifically for orchestrating and automating data pipelines. Azure Data Factory can schedule nightly triggers to copy CSV files from Azure Data Lake Storage Gen2 into an Azure Synapse dedicated SQL pool, and it handles errors through built-in retry policies, activity-level error outputs, and failure notifications. On the DP-900 exam, this scenario tests your understanding of how to automate data loading into Azure Synapse using the right orchestration tool, often appearing as a scenario where you must distinguish between Azure Data Factory (for pipeline orchestration) and Azure Synapse Pipelines (which are actually the same engine but scoped differently). A common trap is choosing Azure Databricks or PolyBase, but remember: if the question says “orchestrate,” “schedule,” or “automate a pipeline,” the answer is almost always Azure Data Factory. Memory tip: “ADF orchestrates the night shift” — it’s the conductor for your scheduled data loads.
DP-900 Describe an analytics workload on Azure Practice Question
This DP-900 practice question tests your understanding of describe an analytics workload on azure. 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.
A retail company receives daily sales data as CSV files in Azure Data Lake Storage Gen2. They need to load this data into an Azure Synapse Analytics dedicated SQL pool every night. The process must be automated, scheduled, and include error handling for failed loads. Which Azure service should they use to orchestrate this pipeline?
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
Azure Data Factory
Azure Data Factory (ADF) is the correct choice because it is a cloud-based ETL and data integration service designed specifically for orchestrating and automating data pipelines. It supports scheduled triggers, can copy CSV files from Azure Data Lake Storage Gen2 into an Azure Synapse dedicated SQL pool, and provides built-in error handling via retry policies, activity-level error outputs, and pipeline failure notifications.
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.
- ✓
Azure Data Factory
Why this is correct
Azure Data Factory is designed for orchestrating data pipelines with scheduling, monitoring, and error handling. It can copy CSV files from Azure Data Lake Storage to Azure Synapse Analytics and handle failures gracefully.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Azure Stream Analytics
Why it's wrong here
Azure Stream Analytics is for real-time stream processing, not for scheduled batch loading of files. It cannot directly load CSV files from storage into Synapse on a nightly schedule.
- ✗
Azure Databricks
Why it's wrong here
Azure Databricks can process data and write to Synapse, but it is a compute engine, not a scheduling and orchestration service. It can be used within a pipeline orchestrated by Data Factory, but alone it lacks native scheduling and error-handling capabilities for simple file loads.
- ✗
Azure Logic Apps
Why it's wrong here
Azure Logic Apps can automate workflows and integrate with various services, but it is better suited for smaller-scale integrations and app workflows. For heavy data movement and transformation at scale, Azure Data Factory is the correct choice.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may confuse Azure Data Factory with Azure Logic Apps because both can schedule and trigger actions, but Logic Apps is designed for lightweight API integrations and lacks the native data movement capabilities and PolyBase support required for bulk loading into a dedicated SQL pool.
Detailed technical explanation
How to think about this question
Under the hood, ADF uses Integration Runtimes (IRs) to perform data movement, and for Azure Synapse Dedicated SQL Pool, it leverages PolyBase or COPY INTO for high-throughput ingestion. ADF’s built-in retry policies can be configured with exponential backoff, and its ‘On Failure’ activity path allows sending alerts via email or triggering alternative logic, ensuring robust error handling. In a real-world scenario, a retail company might use ADF’s tumbling window trigger to run the pipeline nightly at 2 AM, with a failure notification sent to an Azure Monitor alert.
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.
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this DP-900 question test?
Describe an analytics workload on Azure — This question tests Describe an analytics workload on Azure — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Azure Data Factory — Azure Data Factory (ADF) is the correct choice because it is a cloud-based ETL and data integration service designed specifically for orchestrating and automating data pipelines. It supports scheduled triggers, can copy CSV files from Azure Data Lake Storage Gen2 into an Azure Synapse dedicated SQL pool, and provides built-in error handling via retry policies, activity-level error outputs, and pipeline failure notifications.
What should I do if I get this DP-900 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: Jun 11, 2026
This DP-900 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DP-900 exam.
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