Stream processing is a way of analyzing data in real-time as it is generated, rather than storing it first and then analyzing it later. It’s like having a team of workers who process items as they come off an assembly line, rather than waiting for a finished product to be packaged and analyzed.
In computing, data is constantly being generated from various sources such as sensors, social media, or website traffic. Stream processing systems are designed to continuously process this data in small pieces called “events.” Each event can be analyzed and acted upon individually, allowing for quick and efficient processing.
For instance, imagine a company that wants to monitor customer behavior on its website in real-time. By using stream processing, they can analyze the data as it’s generated and gain insights into which products or pages are being visited most frequently. This allows them to make real-time decisions, such as making product recommendations to customers as they browse the site.
Stream processing can also be used in other applications, such as detecting fraud in financial transactions, monitoring machinery for potential breakdowns, or analyzing social media activity during a live event.
To sum it up, stream processing is a way of analyzing data as it is generated in real-time, allowing for efficient and quick processing and decision-making.
Reference
Stream processing. TechTarget. Updated August 2021 https://www.techtarget.com/searchdatamanagement/definition/stream-processing