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42 of 50 people found the following review helpful
on August 9, 2012
Format: HardcoverVerified Purchase
I am a retired data analysis professional. For the final 15 years of my active career I was involved in the analysis of semiconductor wafer fab production data for advanced process control and fault detection and classification. While the data sets were not huge by today's standards, they were large enough to stretch the application of traditional statistical methods. Subjects such as cluster analysis, missing data estimation, and relatively large predictive models were of interest.

I bought this book hoping to learn something about new analytic tools that have been developed in the past five years or so. Unfortunately, I didn't learn very much. Analytic tools that were mentioned were not described in any detail. I found a few mentions of predictive modeling, a couple of decision trees, and just one of neural networks. All were mentioned by name only, with no explanation of how they are built, where they can be applied, with examples taken from th so-called "real world."

I was also disappointed to find that the total orientation of this book is toward marketing applications. There is no discussion of such big data sets as seismic data, weather forecasting, satellite photo feeds, or large-scale manufacturing systems. In that regard the book is mistitled.

This book is addressed to a non-technical audience, and that is fine. However my test for a book of this kind is that a potential customer of these analytic services should accomplish enough understanding of the tools of the field to be able to conduct an intelligent discussion with a professional practitioner. This book fails that test.
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23 of 27 people found the following review helpful
on July 25, 2012
Format: HardcoverVerified Purchase
Nice, clear intro to the high level concepts of Big Data. Easy, fun read. Gives enough detail for putting together an executive report or getting a team started. Pros and cons are balanced well, examples are interesting and informative (starts off with Web data and moves on to more 'boring' industires like insurance and retail), touches on possible uses of text predictive analytics, MapReduce/Hadoop, a very inspiring section on how to build and sustain a Big Data team, etc.

Bill tackles controversial issues with ease and confidence, giving away his years of practical experience (statistical significance vs business ROI, sampling or not, shoot for improvement not perfection, just get started!, etc.).

Someone said something about the book mentioning but not explaining terms like logistic regression and boosted trees. (1) If you don't know these terms, probably the topic of Big Data would not be of much interest to you. Or maybe start with Bishop Pattern Recognition and Machine Learning (Information Science and Statistics), Hastie The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics), or something similar. (2) There is no single book to prepare someone for the nitty-gritty of this totally new, interdisciplinary subject. If you are familiar with the machine learning, statistical, engineering methods and you need to know more about Big Data, then this book is a good place to start. But if you don't know the basics, you will probably need to build some acumen before reading this or any other similar book on the subject. I'm not affiliated with the author nor his company in any way.
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14 of 17 people found the following review helpful
on May 29, 2012
Format: Hardcover
You don't have to be a "data" manager to benefit from this superb, user friendly guide to big data. Whether you're involved in strategy, marketing, business development, or general management, you'll find some useful insights. The really important theme of this book is the convergence of data management and analytics. It's one thing to generate data, but it's quite another to parse and analyze it. Bill Franks has done a terrific job of putting these issues into context. The bottom line is how do you extract business value from massive and growing amounts of structured and unstructured data? The examples are interesting and it's easy to draw parallels to many other industries.

I found this to be an eye-opening look at a trend that is still in the early stage of emergence - something that will definitely provide competitive advantage to organizations that do this effectively. This is one of those "much appreciated" books on a topic that affects all organizations. Computers and wireless gizmos, digitalization of health records, an explosion of sensors of every shape and function, are all pushing us into new uncharted waters. Bill Franks helps provide some guideposts. I don't get time to read many "business books" but this one made my list. I also enjoyed the interviews with Bill Franks on YouTube!
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7 of 9 people found the following review helpful
on April 12, 2012
Format: Hardcover
I am a marketing professional and use data all the time to make decisions. I rely on other team members with technical background to validate consumer insights via all the data my company has. I need people who do deeper analytic to support me. Big data is a topic that intrigues me, so I decided to check this book out. My main concern going in was that it would be way over my head. I was pleasantly surprised at the way the topics are presented. There were a few spots where the technical details escaped me, but overall, I got most of the concepts and how they can apply to my situation. I may not be someone who will be doing these analytic personally, but I will be working with those who produce them. And, more importantly, needing to apply the analytic as part of my job. This was a great book for someone like me to gain an overall understanding of what big data is all about and how a company like mine can effectively capture and analyze it. Mr. Frank's must have had marketers in mind when he wrote his book. I would highly recommend it.
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5 of 6 people found the following review helpful
on July 26, 2012
Format: HardcoverVerified Purchase
Bill does a great job striking the right balance between technology and business. Too often, books are either pure fluff or pure techno babble. I also really liked one of the core messages of the book: be practical and just get stuff done (e.g. commodity models). The framing of the new possibilities with web, mobile, RFID, smart grids etc. data was particularly good. And on the whole, a very balanced book without talking too much about specific vendors, which was a concern given the Wiley and SAS angle.
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2 of 2 people found the following review helpful
on June 2, 2012
Format: Hardcover
This book is targeted for the business managers who wish to capitalize on opportunities that Big Data can enable within their business. It is written is an easy, clear, flowing manner that motivates and mentors the non-technical person about the complex issues surrounding Big Data.

Franks continually focuses on the key success factor... How can companies improve their business enabled by analytics that probe this Big Data?

The book outlines the relevant technologies (such as the analytical sandbox) and finishes by suggesting practical actions that will improve three areas: develop great analysts, build a great analytic team, and foster an analytic culture within your organization. Franks concludes with three simple principles for stimulating discovery and innovation: breaking out of the box, riding the ripples, and aligning to a common target.

I highly recommend this book if you are a high-tech executive concerned about impacts of Big Data on your company and industry.
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2 of 2 people found the following review helpful
on April 26, 2012
Format: Hardcover
I am a chemical engineer dealing with floods of data on a daily basis. This book covers the complicated subject of today's "Big Data" analysis in a conversational and interesting fashion. The thrust is not algorithmic or technical analysis methods, but rather how to build an analytical environment capable of dealing with the huge volumes of data pouring into any application. With new technologies comes ever more data flooding into our workspace and this book teaches how to manage that data, build a strong analytical team and gives many of the pitfalls that bog down an organization during analysis. The subject is relevant for engineers, statisticians, grocery store managers and everyone in between. This book was enjoyable to read and I highly recommend it.
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6 of 8 people found the following review helpful
on June 7, 2012
Format: HardcoverVerified Purchase
I read this book in preparation for several invited talks I gave about the intersection of Big Data, visualization and analytics. This is an excellent, largely non-technical view of this exploding area. In particular I like how it addresses the integration of analytical expertise to business. An easy read that can be read in parts to address your company needs. That advice can be used whether your data is 'big' or not. The types of data sources and how they can be combined are also well covered.

Also useful was the authors description and advice on constructing analytics teams and an 'analytics innovation center' and how resources can be used to staff and empower this idea. Discussed is the need to understand and promote an analytics culture that will promote the resulting improvement. Good thoughts there .... we implemented aspects of this in our company, where the centers were set up to address particular kinds of data for specific functional parts of our enterprise. That was done because the ready access to key data sources and subject matter expertise was important to making the idea work

This book is a great introduction to the subject. Managers should read it. All technology areas like this exist on quickly shifting ground ... but this is a case where the analytics part is not shifting as quickly, and can often be used in a plug-and-play way to address business process improvement. So this book will be useful for a long time to come, when integrated with other online and vendor resources that keep you up to date. Also many and varied industry examples. Pick one that is closest to your industry and explore it in detail. I used a number of points from this book in my talk, and the ensuing conversations led to several next steps. Excellent book for an introduction to this space.
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4 of 5 people found the following review helpful
on June 10, 2012
Format: Hardcover
This book focuses on extracting business value from Big Data, which sets it apart from most others in this field. It's also highly readable and `user-friendly' - as if the author is talking to you personally.
If you're looking for formulae or algorithms, then this book probably isn't for you. But if you're looking for commonsense explanations of why Big Data is important, the different sources of Big Data, issues to consider and ways in which Big Data can add value, then I'd recommend it highly.
On top of that, there are sections on how to carry out large-scale analytics effectively, covering practical, organisational and cultural issues - that books on data mining usually omit.
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1 of 1 people found the following review helpful
on November 6, 2013
Format: Hardcover
If you are looking for a book that gives you an intro to the world of big data, this is the one to get. I teach a hospitality class on Big Data and this is the book I have the students read. The author does a really good job of going through the various aspects of what big data is, but more importantly he gives anecdotal stories to relate them back. Each chapter has a summary which highlights the main points of each chapter. This makes it easy to follow along and is almost like having cliff notes for each section. I recommend this book for anyone who wants a leisurely read about big data or even for other teachers out there who are looking for an intro book to the subject. This is the type of book that when after you read it, you want to immediately learn more about the topic and also realize just how relevant it is.
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