Question 1mediummultiple choice
Full question →mediummultiple choiceObjective-mapped
A company receives daily sales data from multiple retail stores as CSV files that are uploaded to Azure Blob Storage. The data must be cleansed, validated, and aggregated before being loaded into Azure Synapse Analytics for reporting. The transformations involve complex business logic and must run reliably every night. The company wants a service that can orchestrate and execute the entire pipeline with minimal development effort. Which Azure service should they use?
Answer choices
Why each option matters
Good practice is not just finding the correct option. The wrong answers often show the exact trap the exam wants you to fall into.
A
Best answer
Azure Data Factory with mapping data flows
Azure Data Factory provides schedule-based orchestration and mapping data flows to perform complex transformations without coding. It integrates seamlessly with Azure Synapse Analytics for loading transformed data.
B
Distractor review
Azure Stream Analytics
Azure Stream Analytics is designed for real-time stream processing, not for scheduled batch transformations of files. It is not suitable for this nightly batch workload.
C
Distractor review
Azure Databricks
Azure Databricks can transform data using notebooks, but it lacks built-in orchestration for scheduling and monitoring pipelines. Additional setup is needed, making it less efficient than Azure Data Factory for this requirement.
D
Distractor review
Azure Logic Apps
Azure Logic Apps is for workflow automation and integration, not for heavy data transformations and large-scale ETL. It is not designed to handle complex data cleansing and aggregation operations.
Common exam trap
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Technical deep dive
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- 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.
Related practice questions
Related DP-900 practice-question pages
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
More questions from this exam
Keep practising from the same exam bank, or move into a focused topic page if this question exposed a weak area.
Question 1
A data engineer needs to process streaming data from IoT devices and store the results in Azure Data Lake Storage for long-term analytics. The data must be processed in near real-time to detect anomalies and trigger alerts. Which Azure service should the engineer use for stream processing?
Question 2
A data engineer needs to query data stored in CSV files in Azure Data Lake Storage Gen2 using T-SQL in Azure Synapse Analytics, without loading the data into the database. Which feature should they use?
Question 3
A data engineer needs to process raw clickstream data from multiple websites that is stored in Azure Blob Storage as JSON files. The processing must run automatically every hour, transform the data into a structured format for reporting, and handle schema changes in the source data without manual intervention. Which Azure service should be used?
Question 4
A data engineer is designing a data lake architecture in Azure. They plan to first ingest raw data from various sources into a landing zone in Azure Data Lake Storage Gen2. Then they will clean, validate, and deduplicate that data in a second zone. Finally, they will create aggregated, business-ready datasets in a third zone for analysts. This layered approach is known as which architecture?
Question 5
A data engineer needs to transform large datasets stored in Azure Data Lake Storage Gen2 using Python and Apache Spark. They want a serverless compute option that automatically scales and requires no cluster management. Which Azure service should they use?
Question 6
A company collects customer feedback forms. Each form contains always-present fields like CustomerID and SubmissionDate, but also a free-text Comments field and optional fields like Rating or ProductCategory that vary between forms. How should this data be classified?
FAQ
Questions learners often ask
What does this DP-900 question test?
Read the scenario before looking for a memorised answer.
What is the correct answer to this question?
The correct answer is: Azure Data Factory with mapping data flows — Azure Data Factory is a cloud-based ETL service that orchestrates data movement and transformation at scale. It can schedule pipelines to run nightly, perform data flows for cleansing and aggregation, and load results into Azure Synapse Analytics. This makes it the best fit for the batch transformation scenario.
What should I do if I get this DP-900 question wrong?
Then try more questions from the same exam bank and focus on understanding why the wrong options are tempting.
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