Question 1mediummultiple choice
Full question →mediummultiple choiceObjective-mapped
A company has a data warehouse in Azure Synapse Analytics dedicated SQL pool. They need to load new sales data every night from a CSV file stored in Azure Data Lake Storage Gen2. The load process must be automated, scheduled, and have error handling for failed loads. Which Azure service should they use to orchestrate this process?
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
Azure Data Factory provides pipeline orchestration with scheduling, triggers, and error handling. It can copy data from ADLS Gen2 to Synapse dedicated SQL pool using the 'Copy Data' activity or stored procedure activities.
B
Distractor review
Azure Stream Analytics
Azure Stream Analytics processes real-time streaming data using SQL-like queries. It is not designed for scheduled batch loading of files from a data lake.
C
Distractor review
Azure Databricks
Azure Databricks is a Spark-based analytics platform that can perform data transformations and writes, but it lacks built-in scheduling and orchestration features that are available in Azure Data Factory.
D
Distractor review
Azure Logic Apps
Azure Logic Apps is best for automating workflows between applications (e.g., email, Office 365). It can integrate with Azure services but is not the ideal tool for complex data warehouse loading pipelines.
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 the primary cloud-based ETL/ELT service for orchestrating data movement and transformation. It supports scheduling, monitoring, and error handling, and has built-in connectors for Azure Synapse and ADLS Gen2. Azure Stream Analytics is for real-time data processing. Azure Databricks is for Spark-based data engineering but lacks native scheduling and pipeline orchestration. Azure Logic Apps is for workflow automation across apps, not optimized for data warehouse loading.
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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