- A
Azure Data Factory
Azure Data Factory provides orchestration and scheduling for data pipelines. It can copy data from on-premises sources, run custom processing (like PySpark on Databricks), and load results into Synapse Analytics.
- B
Azure Stream Analytics
Why wrong: Azure Stream Analytics is designed for real-time stream processing, not for batch orchestration with hourly scheduling and diverse compute steps.
- C
Azure Logic Apps
Why wrong: Azure Logic Apps is for workflow automation, often integrating with SaaS applications. It lacks the native data movement capabilities and integration with big data compute services needed for complex ETL pipelines.
- D
Azure Databricks
Why wrong: Azure Databricks is a big data analytics platform that can run PySpark notebooks, but it does not provide built-in orchestration, scheduling, or data movement capabilities. It would need an external orchestrator like Data Factory.
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 data engineer needs to build a pipeline that runs every hour, copies new sales data from an on-premises SQL Server to Azure Data Lake Storage Gen2, transforms the data using PySpark, and then loads it into Azure Synapse Analytics dedicated SQL pool. Which Azure service should be used to orchestrate the entire 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 to orchestrate complex pipelines. It can copy data from on-premises SQL Server via a self-hosted integration runtime, trigger the pipeline on an hourly schedule, execute PySpark transformations in Azure Databricks or HDInsight, and load the results into Azure Synapse Analytics dedicated SQL pool—all within a single, managed orchestration workflow.
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 provides orchestration and scheduling for data pipelines. It can copy data from on-premises sources, run custom processing (like PySpark on Databricks), and load results into Synapse Analytics.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Azure Stream Analytics
Why it's wrong here
Azure Stream Analytics is designed for real-time stream processing, not for batch orchestration with hourly scheduling and diverse compute steps.
- ✗
Azure Logic Apps
Why it's wrong here
Azure Logic Apps is for workflow automation, often integrating with SaaS applications. It lacks the native data movement capabilities and integration with big data compute services needed for complex ETL pipelines.
- ✗
Azure Databricks
Why it's wrong here
Azure Databricks is a big data analytics platform that can run PySpark notebooks, but it does not provide built-in orchestration, scheduling, or data movement capabilities. It would need an external orchestrator like Data Factory.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse Azure Databricks (a compute/transform service) with an orchestration service, forgetting that ADF is the dedicated tool for scheduling, copying, and managing the full pipeline lifecycle.
Detailed technical explanation
How to think about this question
Under the hood, ADF uses a self-hosted integration runtime (IR) to securely connect to on-premises SQL Server via port 1433 (default SQL Server port) and supports incremental data loading using watermark columns or change tracking. The pipeline can invoke a Databricks notebook activity to run PySpark transformations, and then use a Copy activity or Stored Procedure activity to load data into Synapse dedicated SQL pool using PolyBase or COPY INTO for high-throughput ingestion. A real-world scenario is a retail company that needs to ingest hourly sales transactions from a local SQL Server, aggregate them in Databricks, and load into Synapse for near-real-time dashboards—ADF handles retries, dependencies, and monitoring across all steps.
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 to orchestrate complex pipelines. It can copy data from on-premises SQL Server via a self-hosted integration runtime, trigger the pipeline on an hourly schedule, execute PySpark transformations in Azure Databricks or HDInsight, and load the results into Azure Synapse Analytics dedicated SQL pool—all within a single, managed orchestration workflow.
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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