Smarter Data Science. Cole Stryker
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Science” to explain why we're underachieving on the promise of AI. Full of practical ideas for improving the practice of information architecture for modern analytical environments using AI or ML. Highly recommended.
Linda Nadeau, Information Architect, Metaphor Consulting LLC
In this book, the authors “unpack” the meaning of data as a natural resource for the modern corporation. Following on Neal's previous book that explored the role of data in enterprise transformation, the authors construct and lead the reader through a holistic approach to drive business value with data science. This book examines data, analytics, and the AI value chain across several industries describing specific use and business cases. This book is a must read for Chief Data Officers as well as accomplished or inspiring data scientists in any industry.
Boris Vishnevsky, Principal, Complex Solutions and Cyber Security, Slalom; Adjunct Professor, TJU
As an architect working with clients on highly complex projects, all of my new projects involve vast amounts of data, distributed sources of data, cloud-based technologies, and data science. This book is invaluable for my real-world enterprise scale practice. The anticipated risks, complexities, and the rewards of infusing AI is laid out in a well-organized manner that is easy to comprehend taking the reader out of the scholastic endeavor of fact-based learning and into the real world of data science. I would highly recommend this book to anyone wanting to be meaningfully involved with data science.
John Aviles, Federal CTO Technical Lead, IBM
I hold over 150 patents and work as a data scientist on creating some of the most complex AI business projects, and this book has been of immense value to me as a field guide. The authors have established the need as to why IA must be part of a systematic maturing approach to AI. I regard this book as a “next generation AI guidebook” that your organization can't afford to be without.
Gandhi Sivakumar, Chief Architect and Master Inventor, IBM (Australia)
A seminal treatment for how enterprises must leverage AI. The authors provide a clear and understandable path forward for using AI across cloud, fog, and mist computing. A must read for any serious data scientist and data manager.
Raul Shneir, Director, Israel National Cyber Directorate (Israel)
As a professor at Wharton who teaches data science I often mention to my students about emerging new analytical tools such as AI that can provide valuable information to business decision makers. I also encourage them to keep abreast of such tools. Smarter Data Science will definitely make my recommended readings list. It articulates clearly how an organization can build a successful Information architecture, capitalizing on AI technologies benefits. The authors have captured many intricate themes that are relevant for my students to carry with them into the business world. Many of the ideas presented in this book will benefit those working directly in the field of data science or those that will be impacted by data science. The book also includes many critical thinking tools to ready the worker of tomorrow … and realistically, today.
Dr. Josh Eliashberg, Sebastian S. Kresge Professor of Marketing, Professor of Operations, Information, and Decisions, The Wharton School
This is an excellent guide for the data-driven organization that must build a robust information architecture to continuously deliver greater value through data science or be relegated to the past. The book will enable organizations to complete their transformative journey to sustainably leverage AI technologies that incorporate cloud-based AI tools and dueling neural networks. The guiding principles that are laid out in the book should result in the democratization of data, a data literate workforce, and a transparent AI revolution.
Taarini Gupta, Behavioral Scientist/Data Scientist, Mind Genomics Advisors
Smarter Data Science
Succeeding with Enterprise-Grade Data and AI Projects
Neal Fishman with Cole Stryker
Copyright © 2020 by John Wiley & Sons, Inc., Indianapolis, Indiana
Published simultaneously in Canada
ISBN: 978-1-119-69341-3
ISBN: 978-1-119-69438-0 (ebk)
ISBN: 978-1-119-69342-0 (ebk)
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About the Authors
Neal Fishman is an IBM Distinguished Engineer and is the CTO for Data-Based Pathology within IBM's Global Business Services organization. Neal is also an Open Group Certified Distinguished IT Architect. Neal has extensive experience working with IBM's clients across six continents on complex data and AI initiatives.
Neal