Real-time Data Processing

Real-time data processing refers to the ability to process data as soon as it is generated, without any delay. This involves the use of technologies and techniques that enable the processing of data in real-time, such as stream processing, complex event processing, and in-memory data grids. Real-time data processing is essential in many applications, such as fraud detection, stock trading, and IoT devices, where immediate action is required based on the data generated. It involves the use of distributed systems and parallel processing to handle large volumes of data in real-time. Real-time data processing requires high-speed data ingestion, low-latency processing, and real-time analytics to provide insights and actions based on the data generated.
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