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Big Data, Big Analytics: Emerging Business Intelligence and Analytic Trends for Today's Businesses Hardcover – January 22, 2013


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Editorial Reviews

From the Inside Flap

The Age of Big Data Analytics is here, and these are truly revolutionary times. This timely book looks at cutting-edge companies supporting an exciting new generation of business analytics. This represents a genuine leap forward and a clear opportunity to realize enormous gains in terms of efficiency, productivity, revenue, and profitability.

Written for business managers and executives who want to make the most out of their information resources, Big Data, Big Analytics strikes a careful balance between high-level strategy and sample code, making an otherwise highly technical topic accessible through stories, metaphors, and analogies. The authors—decision science and analytics experts—describe the enabling technology and illustrate the value of Big Data through industry examples. After introducing the people and corporations who are successfully working with Big Data, the book delves deeper into the organization and the roles it takes to make Big Data successful.

In this user-friendly guide, you'll discover:

  • What Big Data is and why it's important
  • Industry examples (Financial Services, Healthcare, etc.)
  • Big Data and the New School of Marketing
  • Fraud, risk, and Big Data
  • Big Data technology
  • Old versus new approaches
  • Open source technology for Big Data analytics
  • The Cloud and Big Data
  • Predictive analytics
  • Crowdsourcing analytics
  • Computing platforms, limitations, and emerging technologies
  • Consumption of analytics
  • Data visualization as a way to take immediate action
  • Moving from beyond the tools to analytic applications
  • Creating a culture that nurtures decision science talent
  • A thorough summary of ethical and privacy issues

The availability of Big Data, low-cost commodity hardware, new information management, and analytic software has produced boundless opportunities for your organization to jump ahead of the competition. Discover how to analyze astonishing data sets quickly and cost-effectively with the tools and strategies found in Big Data, Big Analytics.

From the Back Cover

Praise for Big Data, Big Analytics

"The perfect amount of detail, told in a way that provides insight into an ever-changing business landscape with real-world application—no matter your area of expertise."
— Frank Blake, Chairman and CEO, The Home Depot

"Big Data is like a giant pile of puzzle pieces. And once brought together into context . . . the unfolding picture enables smarter action and ultimately better business outcomes. This is a timely and well-written book for business and IT executives to get up to speed on the Big Data world!"
—Jeff Jonas, IBM Fellow and Chief Scientist, IBM Entity Analytics

"Big Data impacts all of us, and this book is a well-written compilation of what you need to get started. Michael and his team capture the essence of Big Data in an easy-to-digest fashion that should be shared with your entire executive team."
—Mike Blake, CIO, Hyatt

"Every day, companies create enormous quantities of data from various disparate sources—websites, sales teams, social media, digital pictures and multimedia, transactional records, etc. This book is essential for business and IT executives to begin to get their arms around 'Big Data' and how it will change the competitive business landscape."
—Joe Choti, CTO, Major League Baseball Advanced Media

"Big Data is transforming the modern business world. It dictates how banks grant loans, how hedge funds make trades, and much else. Big Data, Big Analytics gives readers a clear explanation of everything they need to know, from what Big Data is to the technology and how it should be used."
—Anthony Goldbloom, founder and CEO, Kaggle

"As a professor of customer intelligence, this book will help my students understand the multidisciplinary nature of Big Data and how to solve problems, better serve customers, and make their companies smarter. Highly recommended reading!"
—Tony Branda, a founder of Pace University's Customer Intelligence MS Program

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Product Details

  • Hardcover: 224 pages
  • Publisher: Wiley; 1 edition (January 22, 2013)
  • Language: English
  • ISBN-10: 111814760X
  • ISBN-13: 978-1118147603
  • Product Dimensions: 6.3 x 0.8 x 9.3 inches
  • Shipping Weight: 15.2 ounces (View shipping rates and policies)
  • Average Customer Review: 3.9 out of 5 stars  See all reviews (20 customer reviews)
  • Amazon Best Sellers Rank: #79,005 in Books (See Top 100 in Books)

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Customer Reviews

3.9 out of 5 stars

Most Helpful Customer Reviews

20 of 20 people found the following review helpful By Rocaveli on May 1, 2013
Format: Hardcover Verified Purchase
Being a bit unfair: this book reads like quotes from blog posts written by people with fancy titles at big companies. I was expecting a bit more insight and actionable guidance, instead I got the same "big data is weally weally impo'tant" refrain that CIOs are fond of singing. The book seems to be written for folks of a prior generation: the author is constantly trying to dumb down big data as if explaining color to a color-blind kid. Unfortunately this predisposes the book to repeating many of the same generalizations we have all heard many times, and yet failing as an introductory text because it relies on a lot of prior knowledge from the "old way" of doing things (which the author constantly compares and contrasts big data to). The big data book I'm looking for needs to be written by a native of big data, someone who can write about the possibilities from an embedded perspective. This book all too often seems like it's translating to and from an archaic language with a limited vocabulary - which inherently limits the concepts and perspectives that are explored by the book, and in fact it limits the author's perspective on what's possible with big data in the first place.
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19 of 23 people found the following review helpful By Thomas Dinsmore on January 18, 2013
Format: Hardcover Verified Purchase
Books on Big Data tend to fall into two categories: they are either "strategic" and written at a very high level, or they are cookbooks that tell you how to set up a Hadoop cluster. Moreover, many of these books focus narrowly on data management -- an interesting subject in its own right for those who specialize in the discipline, but yawn-inducing for managers in Sales, Marketing, Risk Management, Merchandising, Operations who have businesses to run.

Hey, we can manage petabytes of data. Thank you very much. Now go away.

Big Data Big Analytics appeals to business-oriented readers who want a deeper understanding of Big Data, but aren't necessarily interested in writing MapReduce code. Moreover, this is a book about analytics -- not just how we manage data, but what we do with it and how we make it drive value.

The authors of this book -- Michael Minelli, Michele Chambers and Ambiga Dhiraj -- combine in-depth experience in enterprise software and data warehousing with real-world experience delivering analytics for clients. Building on interviews with a cross-section of subject matter experts -- there are 58 people listed in the acknowledgements -- they map out the long-cycle trends behind the explosion of data in our economy, and the expanding tools to manage and learn from that data. They also point to some of the key bottlenecks and constraints enterprises face as they attempt to deal with the tsunami of data, and provide sensible thinking about how to address these constraints.

Big Data Big Analytics includes rich and detailed examples of working applications. This is refreshing; books in this category tend to push case studies to the back of the book, or focus on one or two niche applications.
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5 of 5 people found the following review helpful By EA Specialist on September 12, 2013
Format: Hardcover
Books provides a very basic overview of Big Data and openly markets a Consulting Company. There are better books worth your precious dollars and time.
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6 of 7 people found the following review helpful By tcq on July 28, 2013
Format: Hardcover Verified Purchase
The writers throw out a lot of jargon without explanation and convey little useful information. And it's difficult to read because it was so poorly written and so lightly edited. Maybe it's useful to an SVP as a way to pick up a new acronym or two. But it has little value for a data warehouse guy who likes to read.

Here's a sample. It's typical of what you'll find:
"Think about this as having a pipe with a 10-inch diameter and having to squeeze 50 TB of Big Data through the pipe in five minutes in order to provide the service level agreements (SLAs) that your business requires when it would take a 100-inch pipe to meet the SLAs." Huh? If this 'metaphor' doesn't bother you, buy the book.
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1 of 1 people found the following review helpful By KC on February 15, 2014
Format: Hardcover
On the positive side, the book contains a lot of buzz words, catchy phrases in the field that can certainly help the reader embellish his/her vocabularies. On the negative side, the book hardly explains much. The majority of its contents are made of quotes, interviews, blogs, articles, and, unfortunately for the reader, not much explanation and analysis follow. Take page 72 as an example. On page 72 alone, it quotes an article form Tech Target, followed by tale (somewhat irrelevant) of Brocklebank’s startup, ended with an interview of a CEO. The next section continues with another interview of an SVP which lasts for two pages. The cycle repeats. All in all, the book is a just a compilation of disjoint pericopes of remarks.
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1 of 1 people found the following review helpful By GeoVizer on June 5, 2014
Format: Hardcover
The very first sentence is a run-on and it got worse from there. I give the authors credit for being interested in the right topics, but I could not stomach the sloppy writing style enough to read it straight through. So, I tried dipping into the book at a few points to try and find the "content", but it felt fluffy everywhere. I wasn't learning anything. Too much marketing, not enough engineering, at least for my needs. I've been interested in Big Data (and analytics) for a while, so maybe I'm not the right audience for this book.
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By DP on May 4, 2015
Format: Hardcover Verified Purchase
I have not read this entire book as of yet but I can tell you that the authors have not decided what their target audience is for this book. In some cases they use a lot of big words and concepts that are at the core of how it all works, and in the same chapter they bring up how data storage is measured as well as other unrelated information such as an ASCII to binary conversion table. These are concepts that anyone remotely interested in this field would very likely already know about.
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