DP-900 Describe core data concepts Practice Question
A hospital collects patient vital signs every minute using IoT sensors. Each reading contains a timestamp, patient ID, heart rate, blood pressure, and temperature. This data is ingested continuously for real-time monitoring and alerting. Which type of data workload does this scenario best represent?
⚠ Common exam trap
Candidates often confuse 'real-time streaming' with 'analytical workload' because both involve data processing, but analytical workloads are designed for historical analysis and reporting, not for sub-second alerting on live data streams.
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
✓
D. Real-time streaming
This scenario requires continuous ingestion of sensor data with immediate processing for real-time monitoring and alerting. Real-time streaming workloads, such as those handled by Azure Stream Analytics or Apache Kafka, are designed to process unbounded data streams with low latency, making option D correct.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
A. Transactional workload
Why it's wrong here
Transactional workloads involve OLTP systems where individual records are inserted, updated, or deleted in real time with strict consistency. While the sensor data is ingested in real time, the primary purpose is monitoring and alerting, not transactional updates that require ACID guarantees across multiple related tables.
- ✗
B. Analytical workload
Why it's wrong here
Analytical workloads typically involve querying and aggregating large volumes of historical data to support business intelligence or reporting. The sensor data here is used for real-time monitoring rather than historical analysis, so this does not fit an analytical workload.
- ✗
C. Batch processing
Why it's wrong here
Batch processing is a data processing model where data is accumulated over a period (e.g., hourly, daily) and then processed in bulk at scheduled intervals. The hospital's IoT sensors emit a continuous stream of vital-sign readings every minute, and the workload requires immediate ingestion and action—such as triggering alerts or updating dashboards—rather than waiting for a batch window. Even if a batch job could later analyze historical trends, the primary processing pattern here is one of continuous, low-latency handling, so calling it 'batch processing' mischaracterizes the system's real-time operational requirement. A batch approach would introduce unacceptable latency for time-critical patient monitoring.
- ✓
D. Real-time streaming
Why this is correct
Real-time streaming workloads handle continuous data flows that are processed as soon as they arrive, often with low latency requirements. The hospital's IoT sensors generate data every minute that must be acted on promptly, making this a clear example of a real-time streaming workload.
Go deeper
Related to this question
Learn chapter
Data Roles and Core Concepts
Key term
Data
Data is raw, unprocessed information, like numbers, words, or measurements, that can be stored, processed, and analyzed by computers.
Key term
Azure Stream Analytics
Azure Stream Analytics is a fully managed, real-time data processing service that analyzes and transforms high volumes of streaming data from various sources to deliver low-latency insights and trigger actions.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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