What Is Event Stream Processing?
The amount of data being generated in the world is staggering. An estimated 79 zettabytes [1] of data will be generated in 2025, and that number is expected to grow in the coming years. The data can come from a variety of sources, including sensors, video processing, applications, and social media [2]. This is where Event Stream processing can help analyze data at the source, or in transit, to analyze, verify, transform, enrich, and or validate the data.
Image by Jörg Vieli from Pixabay
Traditionally, data has been processed in batches, with data collection over a period of time and then processing all at once. However, this approach is not ideal for large volumes of data that are in a constant state of flux, where not all data is relevant or complete, or where data can be out of date very quickly. Event streaming processing is an approach to data processing that is designed to handle large amounts of data that are constantly changing. [3]
With event streaming processing, businesses can make decisions and take action in real-time. This can give them a competitive advantage by allowing them to react faster to changing markets. It can help businesses improve their efficiency. By processing data in real-time, businesses can avoid storing large amounts of data. This can save companies money and space, improve their customer experience, and provide personalized experiences to their customers.
Common use cases for streaming processing include Fraud detection: Event streaming processing can be used to detect fraud in real-time. For example, a bank could use event streaming processing to track transactions and identify suspicious activity. Customer Behavior Analysis: Event streaming processing can be used to analyze customer behavior in real-time. For example, a retailer could use event streaming processing to track customer foot traffic and identify trends. IoT applications: IoT applications are well suited to event-streaming processing. For example, a smart city could use event streaming processing to collect data from sensors and take action in real-time.
Nowadays it is still a challenge to develop, operate and integrate stream processing systems into the business workflows. Monitoring, fine tuning for cost efficiency, handling backpressure and fault tolerance among many of the challenges are still part of the day-to-day work for developers and operators even when selecting cloud solutions.
Event Streaming Processing stands as a critical technology in the digital age, driving real-time communication and processing. As we’ve seen, its potential is limitless, enabling organizations to streamline processes, respond quickly, and improve user experiences. By embracing Event Streaming, organizations can have real-time insights and continue to innovate in an ever-evolving digital landscape.
References
[1] Internet of Things and data placement
[2] State of IoT 2023: Number of connected IoT devices growing 16% to 16.7 billion globally