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Free Download , by Arvind Sathi

Free Download , by Arvind Sathi

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, by Arvind Sathi

, by Arvind Sathi


, by Arvind Sathi


Free Download , by Arvind Sathi

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, by Arvind Sathi

Product details

File Size: 3142 KB

Print Length: 98 pages

Page Numbers Source ISBN: 1583473807

Publisher: Mc Press (November 15, 2012)

Publication Date: November 1, 2012

Language: English

ASIN: B00A2FOP04

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Amazon Best Sellers Rank:

#1,157,163 Paid in Kindle Store (See Top 100 Paid in Kindle Store)

I think this is a nice book for the high-level exec who needs names, terminology, and problem-situating for Big Data Analytics. Its premise - which I think is a good one - is that the reader is going to be embedded in the already existing B2B and B2C data structures, architecture, and infrastructure already entrenched in the business/consumer world. I don't think there's much here for a data scientist, except in the sense it gives you the vernacular executives use to speak of, and frame, their discipline. But for the exec who needs to know why Big Data poses challenges and opportunities, this is a very digestible approach. It's an "airplane book" for the busy executive.

In case you missed the small print below, this book is a mere 73 pages. It makes for a good short introduction to the topic. But if you are at the stage where you are considering buying a book on Big Data, you will probably want to invest in something more substantial.

When I first got the book from Amazon (on time - USPS not UPS), I thought I got the CD version. The book's really thin. Did I get ripped-off? However, after reading the material, I realized the author had delivered a service by not overwhelming the reader with irrelevant words - every sentence had value! The author does a fantastic job in outlining the application of BigData, and the technologies required. The book does not provide details on the algorithms used in big data analytics - rather it provides a basic framework. I would suggest this to business managers who may not necessarily be implementing a process, but are interacting with colleagues and vendors on the topic. As a loyal IBM employee, the author does plug a few IBM technologies, but tries not to go overboard in promoting them.

The book - or the leaflet, since there are very few pages - has some very interesting information dispersed at various point but at some point, reading an IBM advertising does not fit with expectations ...

Good book to startTo have the bird view of a new subject is always the good startReally appreciate

Written by an IBMer, practical, not visionary. Read something from a Google type young genius! This is written like a users manual.

In my mind this book is definitely the most important and practical guide for Beginners to Big Data Analytics. It covers a very good basics and foundational aspect of Big Data while presenting a strong practical business use cases with advanced analytics concepts.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 businessesIf 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!

The articles on Big Data and its business implications are increasing in its frequency in the popular press. However Dr Arvind's books is a great book to understand its full scope. This is an important topic for everyone to understand, not just for the Analytics team in an organization. This 73-page 7-chapter book is written in first person and reads so engagingly. Everyone who is a business or IT leader needs to understand the opportunities and challenges with Big Data. This book lays that out very well and it addresses topics from the socio-economic drivers to interesting scenarios as to how it is used by early adopters. The entire book can be read by a business reader including the chapters on architecture and implementation.

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