Cognitive Computing and Big Data Analytics

Cognitive Computing and Big Data Analytics by Lucie Masocha
Englis | 2022 | ISBN: 1682517489 | 362 pages | PDF | 2.96 Mb
Cognitive Computing is the use of computational learning systems to augment cognitive capabilities in solving real world problems. Cognitive computing (CC) makes a new class of problems computable. It addresses complex situations that are characterized by ambiguity and uncertainty; in other words it handles human kinds of problems. In these dynamic, information-rich situations data tends to change frequently, and it is often conflicting. Cognitive computing can be utilized to reduce the shortcomings of the concerns faced during big data analytics. Nowadays, people, computers, smart devices, appliances and objects are connected each other in a large and very complex information driven eco system. The era of big data is the basis for innovative cognitive solutions that cannot rely on traditional systems. While traditional computers must be programmed by humans to perform specific tasks, cognitive systems will learn from their interactions with data and humans. Not only is Cognitive Computing a fundamentally new computing paradigm for tackling real world problems, exploiting enormous amounts of data using massively parallel machines, but also it engenders a new form of interaction between humans and computers. In fact, due to the many enabling technologies, social phenomena and economic factors such as the continuous advancements in electronics, the ever-growing computing power of microprocessors, the availability of fast and large memory supports at affordable costs, the prompted miniaturization, the compelling innovation in network infrastructures and networking, a huge amount of data springs from a variety of different sources and is spread at dramatically high speed. New technologies such as cognitive computing offer promise for addressing this challenge because cognitive solutions are specifically designed to integrate and analyze big datasets.