Machine learning (ML) on the Internet of Things (IoT) streaming data toward real-time insights

Abstract

The world generates an unfathomable amount of data every day. The speed with which the data gets generated, transmitted, ingested, and crunched is nothing but spectacular in the recent past. Expert thinkers and pundits across the globe are of the opinion that data is the transformation agent. Data is positioned as a strategic asset for any institution, innovator, and individual to grow and glow and is being reasoned as the new fuel for bringing in real and sustainable business transformation. It is a universally accepted fact that data can be methodically processed, mined, and analyzed to produce actionable insights. There are batch and real-time data processing methods to make sense of data heaps. Further on, there are integrated data analytics platforms in plenty, to extract hidden patterns, associations, and other useful insights out of data volumes. The data analytics ecosystem grows continuously considering the importance of data-driven insights and insights-driven decisions for businesses as well as people to be agile, adaptive and adroit in their dealings and deeds.Off late real-time data capture, storage, analytics, decision-making, and action are being insisted upon vehemently considering the evolving business dynamics. Any data or message has to be carefully captured, cleansed, and crunched immediately in order to be really beneficial for businesses and commoners. It is indisputable that the data value goes down sharply with time. Another facet is that agile and autonomous business systems are extremely event-driven. That is, any business event may trigger a suite of events across. Thus, all kinds of event data/messages have to be received and processed in real time in order to activate and automate one or more business operations. In short, for envisaging and realizing real-time services, applications and enterprises, real-time data analytics capability is very much indispensable. Enterprises are therefore keenly strategizing and setting up analytics infrastructure modules with all the clarity and alacrity to make sense out of both internal and external data in time. Such a futuristic and flexible capability helps business houses to be sagaciously steered in the right direction.