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Big Data: A Revolution That Will Transform How We Live, Work, and Think Paperback – March 4, 2014
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Amazon Exclusive: Q&A with Kenneth Cukier and Viktor Mayer-Schonberger
Q. What did it take to write Big Data?
A. Kenn has written about technology and business from Europe, Asia, and the US for The Economist, and is well-connected to the data community. Viktor had researched the information economy as a professor at Harvard and now at Oxford, and his book Delete had been well received. So we thought we had a good basis to make a contribution in the area. As we wrote the book, we had to dig deep to find unheard stories about big data pioneers and interview them. We wanted Big Data to be about a big idea, but also to be full of examples and success stories -- and be engrossing to read.
Q. Are you big data’s cheerleaders?
A. Absolutely not. We are the messengers of big data, not its evangelists. The big data age is happening, and in the book we take a look at the drivers, and big data’s likely trajectory: how it will change how we work and live. We emphasize that the fundamental shift is not in the machines that calculate data, but in the data itself and how we use it.
Q. In discovering big data applications, what was your biggest surprise?
A. It is tempting to say that it was predicting exploding manholes, tracking inflation in real time, or how big data saves the lives of premature babies. But the biggest surprise for us perhaps was the very diversity of the uses of big data, and how it already is changing people’s everyday world. Many people see big data through the lens of the Internet economy, since Google and Facebook have so much data. But that misses the point: big data is everywhere.
Q. Is Big Data then primarily a story about economic efficiency?
A. Big data improves economic efficiency, but that’s only a very small part of the story. We realized when talking to dozens and dozens of big data pioneers that it improves health care, advances better education, and helps predict societal change—from urban sprawl to the spread of the flu. Big data is roaring through all sectors of the economy and all areas of life.
Q. So big data offers only “upside”?
A. Not at all. We are very concerned about what we call in our book “the dark side of big data.” However the real challenge is that the problem is not necessarily where we initially tend to think it is, such as surveillance and privacy. After looking into the potential misuses of big data, we became much more troubled by “propensity” -- that is, big data predictions being used to police and punish. And by the “fetishization” of data that may occur, whereby organizations may blindly defer to what the data says without understanding its limitations.
Q. What can we do about this “dark side”?
A. Knowing about it is the first step. We thought hard to suggest concrete steps that can be taken to minimize and mitigate big data’s risk, and came up with a few ways to ensure transparency, guarantee human free will, and strike a better balance on privacy and the use of personal information. These are deeply serious issues. If we do not take action soon, it might be too late.
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Top Customer Reviews
Oren Etzioni, frustrated to learn that many passengers booking a flight after he had, were able to pay less - contrary to conventional wisdom. He then 'scraped' information from a travel website from a 41-day period to forecast whether a price was a good deal or not, founding Farecast to offer this new ability. Etzioni next went on to improve the system by digesting data from a travel stie that covered most American commercial routes for a year - nearly 200 billion flight-price records. Before expanding to hotel rooms, concert tickets and used cars, Microsoft snapped up his firm ($110 million) and incorporated it into it Bing.
New processing technologies like open-source Hadoop allow managing far larger quantities of data. Hadoop uses a computational paradigm named MapReduce (by Google) to divide an application into many small fragments, each of which may be executed on any computer node in a cluster. Visa was able to reduce processing time for two years worth of data (73 billion transactions) from 1 month to 13 minutes using Hadoop.
The authors define 'big data' as things that can be done on a large scale that cannot be done on a smaller one, and see it as offering a major transformation.Read more ›
The only reason why I did not give this a five-star review is that the beginning starts off a bit slow and then the book hits it's stride about midway through. Truthfully, this would be a solid 4 1/2 star review, if Amazon allowed. If you can be patient through the first few chapters, you will not be disappointed. However, if you are completely new to the Big Data revolution, this books would make my top five list of must-reads to get your mind around the phenomenon. The first few chapters do a great job setting the stage.
To the initiated in Big Data, there are some fantastic arguments and well thought out opinions on how the industry should proceed as a whole. Frankly, I know I am wiser and have a more rounded understanding after reading. Should make any Big Data person's bookshelf.
(Just in case the author ever reads this review - I appreciate that you wrote this book for a broad audience. I would love to read some material written by you that is more focused on the issues surrounding Big Data. As an example, I think you could do a great job of writing a book simply on the ethics of data and our responsibilities as data stewards)
Other popularizations up until now only revealed the general flavor of analytics becoming available and applicable through data mining and machine learning. This excellent summarization reveals trends that might otherwise be hidden by the forest of numerical and computational methods and will even be valuable in its observations to expert practitioners caught up in the details of computation.
--Ira Laefsky MSE (Computer Science)/MBA formerly on the Senior Consulting Staff of Arthur D. Little, Inc. and Digital Equipment Corporation
Most Recent Customer Reviews
This is a great book for those of us that are not data engineers. My only complaint with the information is that I believe the author overstates the risks associated with big data. Read morePublished 20 days ago by Raven 007
I enjoyed reading this book. Topics discussed and examples gave a realistic understanding of a subject with a lot of "hype" nowadays, but also with a great value.Published 24 days ago by Maher Al-Khaiyat
Interesting ideas and an important subject, but so excruciatingly badly written I couldn't finish it. I wanted to but kept cringing. Read morePublished 1 month ago by Teka
I listened to the audible version. I found useful info to get a quick grasp on big data concept.Published 1 month ago by Muzaffer Kapanoglu
A very comprehensive review of every topic. Very useful for anybody who is approaching Big Data concepts. Has many examples and references.Published 2 months ago by JUAN A BARRAGAN ROMO
The central theme is Bigdata( BD)tells us what but not why. Here is the catch. The authors don't have to explain causation but just correlation. Read morePublished 2 months ago by YIPLIU