Microsoft Azure Data FundamentalsDescribe core data conceptsEasy
A manufacturing company uses IoT sensors to monitor the temperature and pressure of its machinery. These sensors generate data continuously, and the company needs to analyze this data in real-time to detect anomalies and trigger alerts for potential equipment failures. Which data processing option is MOST suitable for this scenario?
- AOnline Transaction Processing (OLTP)
- BOnline Analytical Processing (OLAP)
- CStream Processing
- DBatch Processing
Show answer & explanationAnswer & explanation
Correct answer: C. Stream Processing
Real-time analysis of continuously generated sensor data for immediate anomaly detection and alerts is the core function of stream processing.
Why the other options are wrong
- A. OLTP is for transactional data, not continuous sensor data analysis.
- B. OLAP is for complex historical analysis, not real-time anomaly detection.
- D. Batch processing is for periodic analysis of large data volumes, not real-time.
Stream Processing
A data processing paradigm where data is processed continuously as it arrives, rather than in batches.
- Handles data in motion, often from IoT devices or clickstreams.
- Enables real-time analytics, anomaly detection, and immediate actions.
- Requires low latency and high throughput.
Memory trick: Streams for Sensors, Not Stagnant Data