Kumar R. Machine Learning and Cognition in Enterprises. Business Intelligence transformed

New York: Apress, 2017. — 316 p.The technology follows business needs and progresses along with it. But not all businesses are very much into the latest technology adoption based on their exact needs and various other reasons. Even so, there is always a bigger chunk of business that actually tries to follow what is needed progressively for them in terms of technology adoption. This is where the confusion starts. When an organization wakes up to look for a change, the technology might be generations ahead from what they are into currently. That is where good consulting capabilities come into the picture. Also, awareness on the part of the CXO and other decision makers is absolutely important. But there might be gaps here as well: technology notoriously progresses in leaps and bounds, and attempting to understand it in terms of how it was earlier won’t help at all.
This book is centered around this problem. This is designed first to provide all the basic knowledge toward understanding machine learning and cognitive computing and the other topics covered. But it also presents a new framework called PEIB (a brandnew framework I have defined in this book), which is designed to help decision makers understand where to start with adopting and adapting these technologies for their specific organizational needs and structures and how to achieve success in this process. This is seen in the core chapter of this book: Chapter 10, Transformation Roadmap. Readers are advised to go progressively through the chapters and build the prerequisite understanding in the right order.