Of big data’s famously challenging three Vs—volume, variety, and velocity—it’s velocity that is poised for an enormous breakout from a glut of information generated by the Internet of things.
Soon, sensors on everything from cell phones to refrigerators will be sending constant streams of data, and there will be opportunities to unlock value and insights by combining streams and analyzing them on the fly. That will enable immediate actions.
Leo Scott, the CTO of the cloud-based stream processing platform BrightContext, said that his company has developed a new stream processing programming language called FunnelCake to give analysts better flexibility to handle the new streams. FunnelCake is a part of BrightContext’s recent 2.0 platform launch.
In this interview with Data Informed staff writer Ian B. Murphy, Scott discusses the difference between real-time analytics and stream processing, use cases for stream processing that he thinks could change the way some industries work, and when a real-time data analytics solution isn’t the right fit. (Podcast run time: 17:12)
Email Staff Writer Ian B. Murphy at firstname.lastname@example.org.
(Editor’s note: due to an issue with our podcast player, the best way to listen to this podcast is to go to this page, and click on the player below the headline, “Stream Processing Poised for Boost from Internet of Things.”)