Technology is constantly evolving. Big Data, for example, went from buzzword to business staple a long time ago, exploding and offering actionable insights on how businesses approach everything from HR to marketing analytics. Today, instead of just using data in retrospective reports or to project future trends, companies are using it to harness that insight in the now. It’s called real-time stream processing—and it just might change everything you thought you knew about Big Data.
Stream processing is a platform that allows businesses to implement rules and procedural approaches to examine real-time data alongside data at rest, ultimately detecting patterns at any given moment. Stream processing goes hand in hand with stream analytics—the ability to conduct a statistical analysis at any point within the data stream.
In short, stream processing allows a company to look at data in all phases—where it’s been, when it’s in motion, and where it’s going. Contrast that to a traditional setup in which data must be indexed and processed before it reaches its destination. Stream processing circumvents those steps, extracting the data while it’s being transferred and connecting it to external sources for timely applications.
Real-time stream processing systems must be robust because, according to Google Cloud, they’re dealing “with data import, processing, storage, and analysis of hundreds of millions of events per hour.” Yes, hundreds of millions per hour. Wondering how that architecture could possibly look? See Google Cloud’s version below.
The concept overall can admittedly be a little dense, so let’s look at some real-world examples to help bring it home.
Electronic trading in the stock market is a classic example of stream processing in motion. As electronic trading is not a new phenomenon by any means, it’s clear even stream processing has undergone its own evolution. Today, stream processing is perfectly suited for the plethora of sensor applications related to the ever-connectedness of the Internet of Things (IoT). Factories that use sensor technology to calculate speed or output based on up-to-the moment data about capacity or energy usage, for example, cannot function without stream processing.
Think of virtually any IoT scenario, and odds are it is rooted in stream processing. Let’s examine some less obvious applications in the business world for some additional perspective:
From those examples, we can glean some key benefits of stream processing:
Just a few short years ago, there weren’t many products on the market that could deliver real-time stream processing. That isn’t the case today—there are a host of options that offer not only stream processing but also management tools, a high degree of scalability, the ability to integrate with other key enterprise technologies, and more.
The future of stream processing is a bright one. Some take it even farther. In fact, Dr. Hossein Eslambolchi, Technical Advisor at Facebook, wrote on LinkedIn “The future of large size data streaming and innovation is more critical than any other innovation for the next decade.” I agree. With the explosion of the IoT and the exponential rise of connected mobile devices, stream processing is so much more than just the next big thing in Big Data. And, if stream processing isn’t already on your radar, it should be.
Additional Sources on This Topic
Big Data: From Buzzword to Business Staple
Cloud, Mobility, Security, And Big Data: The Big Four for Business Growth
Real-Time Stream Processing as Game Changer in a Big Data World
Photo Credit: martinlouis2212 Flickr via Compfight cc
This post was first published on Futurum.
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