Question 851 of 982

Describe an analytics workload on Azure →hardMultiple ChoiceObjective-mapped

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 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?

Question 1hardmultiple choice

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A
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
Azure IoT Hub, Azure Data Factory, Azure SQL Data Warehouse
Why wrong: 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
Azure Event Hubs, Azure Stream Analytics, Azure Cosmos DB
Why wrong: 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
Azure Blob Storage, Azure Databricks, Azure Table Storage
Why wrong: 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.

Full breakdown with real-world context →

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 Event Hubs, Azure Stream Analytics, Azure Synapse Analytics

Azure Event Hubs is designed for high-throughput, low-latency ingestion of streaming data from millions of IoT devices. Azure Stream Analytics provides a SQL-based, near real-time processing engine to detect critical events like abnormal heart rates. Azure Synapse Analytics (formerly SQL Data Warehouse) offers a columnar storage format (e.g., columnstore indexes) optimized for historical analysis and SQL-based reporting by data analysts.

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 Event Hubs, Azure Stream Analytics, Azure Synapse Analytics
Why this is correct
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.
Related concept
Read the scenario before looking for a memorised answer.
✗
Azure IoT Hub, Azure Data Factory, Azure SQL Data Warehouse
Why it's wrong here
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.
✗
Azure Event Hubs, Azure Stream Analytics, Azure Cosmos DB
Why it's wrong here
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.
✗
Azure Blob Storage, Azure Databricks, Azure Table Storage
Why it's wrong here
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 traps

Common exam trap: answer the scenario, not the keyword

The trap here is that candidates often confuse Azure IoT Hub with Event Hubs for high-volume event ingestion, or assume Cosmos DB is suitable for columnar analytics storage, but IoT Hub is for device management and Cosmos DB is row-oriented NoSQL, not optimized for SQL-based historical reporting.

Detailed technical explanation

How to think about this question

Azure Event Hubs uses the AMQP 1.0 protocol for high-throughput ingestion, supporting up to 1 MB per second per throughput unit. Azure Stream Analytics can process events with sub-second latency using a temporal windowing model (e.g., tumbling, hopping, sliding windows) to detect patterns like abnormal heart rate over a 5-second window. Azure Synapse Analytics stores data in columnstore indexes, which compress data by column rather than row, enabling faster analytical queries and up to 10x compression compared to row-based storage.

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 Event Hubs, Azure Stream Analytics, Azure Synapse Analytics — Azure Event Hubs is designed for high-throughput, low-latency ingestion of streaming data from millions of IoT devices. Azure Stream Analytics provides a SQL-based, near real-time processing engine to detect critical events like abnormal heart rates. Azure Synapse Analytics (formerly SQL Data Warehouse) offers a columnar storage format (e.g., columnstore indexes) optimized for historical analysis and SQL-based reporting by data analysts.

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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