concept

Data Streaming

Data streaming is a computing paradigm that involves continuously processing and analyzing data in real-time as it is generated or transmitted, rather than in batches. It enables applications to handle high-velocity data flows from sources like sensors, logs, or financial transactions, allowing for immediate insights and actions. This approach is fundamental for building responsive systems such as real-time analytics, monitoring, and event-driven architectures.

Also known as: Stream Processing, Real-time Data Processing, Event Streaming, Continuous Data Processing, Data Streams
🧊Why learn Data Streaming?

Developers should learn data streaming when building applications that require low-latency processing, such as fraud detection, IoT sensor monitoring, or live recommendation engines. It is essential for handling large-scale, time-sensitive data where batch processing delays are unacceptable, enabling businesses to react instantly to events and trends. Use cases include streaming ETL pipelines, real-time dashboards, and complex event processing in domains like finance, telecommunications, and e-commerce.

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