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Big Data Analytics: Disruptive Technologies for Changing the Game Paperback – February 5, 2013
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About the Author
Dr. Arvind Sathi is a Cognitive Scientist with IBM®'s CognitiveSolutions team. Dr. Sathi received his Ph.D. in Artificial Intelligencefrom Carnegie Mellon University and worked under Nobel Prize winner Dr.Herbert A. Simon. Dr. Sathi is a seasoned professional with more than 20 years of leadership in Information Management architecture anddelivery. He works with IBM clients worldwide to envision and architectcognitive solutions. Prior to joining IBM, Dr. Sathi was the pioneer in developing cognitive solutions at Carnegie Group. At KPMG, he led thedevelopment of Enterprise Integration, MDM, and Operations SupportSystems/Business Support Systems (OSS/BSS) solutions for thecommunications market and also developed cross-industry analyticssolutions, which were implemented in communications services, financialservices, and public services. At IBM, Dr. Sathi has led severalanalytics programs including MDM, data security, advanced analytics, big data and related areas and has provided architecture oversight to IBM's strategic accounts. He has also delivered a number of workshops andpresentations at industry conferences on technical subjects includingIM, Big Data & Advanced Analytics, and he holds two patents in data masking. He has published three books on analytics - CustomerExperience Analytics, Big Data Analytics , and Engaging Customers UsingBig Data and releasing his fourth book titled "Cognitive (Internet of)Things" in October 2016 . He has also been a contributing author in anumber of Data Governance books written by Sunil Soares, and haspublished a article series on Advanced Analytics for IBM DeveloperWorks.
Arvind Sathi is a member of IBM's Academy of Technology.
Top customer reviews
Chapters 3 introduced the big data analytics application while Chapter 4 discusses the architecture components. Chapter 5 - Advanced Analytics Platform and Chapter 6 - Implementation of Big Data Analytics are the most impressive chapters of the book as it takes several business processes that is common in many businesses
If you do not have a fairly good understanding of Big Data Analytics from concept to implementation aspects after reading this text I would be very surprised. The way the case studies are handled and the problems identified and discussed also makes it a true reference book. I think everybody involved in Big Data Analytics should have one on his/her desk.
Thanks Dr. Arvind, Excellent work!