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
Good practice is not just finding the correct option. The wrong answers often show the exact trap the exam wants you to fall into.
Best answer
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.
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Azure Stream Analytics
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.
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Azure Databricks
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.
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Azure Logic Apps
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 trap
Common exam trap: NAT rules depend on direction and matching traffic
NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.
Technical deep dive
How to think about this question
NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.
KKey Concepts to Remember
- Static NAT maps one inside address to one outside address.
- PAT allows many inside hosts to share one public address using ports.
- Inside local and inside global describe the private and translated addresses.
- NAT ACLs identify traffic for translation, not always security filtering.
TExam Day Tips
- Identify inside and outside interfaces first.
- Check whether the scenario needs static NAT, dynamic NAT or PAT.
- Do not confuse NAT matching ACLs with normal packet-filtering intent.
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?
Static NAT maps one inside address to one outside address.
What is the correct answer to this question?
The correct answer is: Azure Data Factory — Azure Data Factory is a cloud-based ETL and data integration service that can orchestrate and automate data movement and transformation. It supports scheduling, error handling, and integrates natively with Azure Data Lake Storage and Azure Synapse Analytics. Other services like Stream Analytics are for real-time streams, not scheduled batch loads.
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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