Final answer:
Data stream management is essential for Big Data and IoT systems, as they both involve handling continuous flows of high-velocity data in real-time. The correct answer to the question is (3) Big Data and IoT.
Step-by-step explanation:
Data stream management is required in systems that collect and process continuous streams of data in real-time. These systems must handle high-velocity data efficiently, often with requirements for low-latency processing and the ability to perform complex event processing. Both Big Data and Internet of Things (IoT) fit these criteria.
Big Data involves the processing and analysis of large volumes of data, which often include data streams from sources like social media feeds, financial markets, and network monitoring. Efficient management is crucial to extract meaningful insights from these streams.
IoT, on the other hand, entails a network of connected devices, each generating continuous streams of data that need to be managed and analyzed, such as sensor readings and telemetry data. This is where data stream management systems play a vital role. Therefore, the correct answer to the question 'Which requires data stream management?' is (3) Big Data and IoT.
When talking about managing device data alone without the Big Data context or the networked environment of IoT, it may not always require a full-fledged data stream management system, particularly if the device data doesn't come in high-velocity streams or doesn't require real-time analytics. However, in the context of IoT, the connected devices' data contribbutes to the data streams that must be managed.