June 1, 2018 | Written by: Preetam Kumar
Categorized: Data Analytics | Data Science
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Today’s generation of cognitive and analytical solutions pack a powerful punch, thanks to their ability to deliver insights as they are requested by decision makers or systems. Many of today’s game-changing solutions provide in-depth insights – ranging from understanding customer intentions, to healthcare measures, to systems performance – at the moment they are needed, which is often in real time. Cognitive and analytics systems can dive deep to draw and deliver inferences on behaviors and patterns.
Streaming analytics bolsters insights
But today’s cognitive and analytical engines systems don’t operate in a vacuum. They require data, and lots of it, to fuel their engines, with much of it fed on a real-time basis. That’s why behind every successful cognitive system or analytical engine is a streaming analytics engine – providing real-time data that is tapped and delivered from any and all selected sources. The success of the various forms of cognitive computing – from artificial intelligence to machine learning to deep learning – rests on the ability to access data that provides a continuous flow of knowledge by which programs and algorithms can adapt and renew.
A new generation of streaming analytics solutions is making such capabilities possible, and with availability in the cloud, is accessible to any existing business environment.
Watch this webinar to learn how to build a streaming analytics dataflow, using a drag-and-drop interface to assemble all the different components (known as “operators”) to transform data into actionable insights.