Question 1hardmultiple choice
Full question →hardmultiple choiceObjective-mapped
A healthcare analytics company receives continuous streams of patient monitoring data from IoT devices. The data must be processed in near real-time to detect critical events (e.g., abnormal heart rate). Processed data is then stored in a columnar format for historical analysis and reporting by data analysts using SQL. Which combination of Azure services should they use for ingestion, processing, and storage?
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 Event Hubs, Azure Stream Analytics, Azure Synapse Analytics
Event Hubs ingests data in real-time. Stream Analytics processes the stream to detect events and transform data. Synapse Analytics provides a columnar data warehouse for historical analysis. This combination fits the requirements exactly.
B
Distractor review
Azure IoT Hub, Azure Data Factory, Azure SQL Data Warehouse
IoT Hub is primarily for device management, not just ingestion. Data Factory is a batch orchestration tool, not designed for real-time processing. While SQL Data Warehouse (now Synapse SQL pool) is columnar, the processing is not real-time.
C
Distractor review
Azure Event Hubs, Azure Stream Analytics, Azure Cosmos DB
Azure Cosmos DB is a NoSQL database that stores data as JSON documents, not in a columnar format. It is not optimized for large-scale analytical queries that data analysts would run using SQL.
D
Distractor review
Azure Blob Storage, Azure Databricks, Azure Table Storage
Azure Blob Storage is not a real-time ingestion service. Azure Databricks can do stream processing but requires cluster management. Azure Table Storage is a key-value store, not columnar, and inadequate for analytical queries.
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 Event Hubs, Azure Stream Analytics, Azure Synapse Analytics — Azure Event Hubs is a scalable event ingestion service capable of handling millions of events per second from IoT devices. Azure Stream Analytics provides serverless real-time stream processing with SQL-like language to detect events and transform data. Azure Synapse Analytics (dedicated SQL pool) is a columnar data warehouse optimized for large-scale analytical queries. This combination meets all requirements. IoT Hub is for device management and bi-directional communication, not just ingestion. Data Factory is a batch ETL orchestrator, not real-time. Cosmos DB is not columnar. Blob Storage is not a columnar data warehouse. Databricks can do processing but is more complex and not serverless. Table Storage is not suitable for analytical queries.
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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