Big Data Now: 2012 Edition

Big Data Now: 2012 Edition

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  • Author: O'Reilly Media, Inc.
  • Publisher: "O'Reilly Media, Inc."
  • ISBN: 1449356680
  • Category : Computers
  • Languages : en
  • Pages : 132

The Big Data Now anthology is relevant to anyone who creates, collectsor relies upon data. It's not just a technical book or just a businessguide. Data is ubiquitous and it doesn't pay much attention toborders, so we've calibrated our coverage to follow it wherever itgoes. In the first edition of Big Data Now, the O'Reilly team tracked thebirth and early development of data tools and data science. Now, withthis second edition, we're seeing what happens when big data grows up:how it's being applied, where it's playing a role, and theconsequences -- good and bad alike -- of data's ascendance. We've organized the second edition of Big Data Now into five areas: Getting Up to Speed With Big Data -- Essential information on thestructures and definitions of big data. Big Data Tools, Techniques, and Strategies -- Expert guidance forturning big data theories into big data products. The Application of Big Data -- Examples of big data in action,including a look at the downside of data. What to Watch for in Big Data -- Thoughts on how big data will evolveand the role it will play across industries and domains. Big Data and Health Care -- A special section exploring thepossibilities that arise when data and health care come together.


Big Data Now: Current Perspectives from O'Reilly Radar

Big Data Now: Current Perspectives from O'Reilly Radar

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  • Author: O'Reilly Radar Team
  • Publisher: "O'Reilly Media, Inc."
  • ISBN: 1449315216
  • Category : Computers
  • Languages : en
  • Pages : 174

This collection represents the full spectrum of data-related content we’ve published on O’Reilly Radar over the last year. Mike Loukides kicked things off in June 2010 with “What is data science?” and from there we’ve pursued the various threads and themes that naturally emerged. Now, roughly a year later, we can look back over all we’ve covered and identify a number of core data areas: Data issues -- The opportunities and ambiguities of the data space are evident in discussions around privacy, the implications of data-centric industries, and the debate about the phrase “data science” itself. The application of data: products and processes – A “data product” can emerge from virtually any domain, including everything from data startups to established enterprises to media/journalism to education and research. Data science and data tools -- The tools and technologies that drive data science are of course essential to this space, but the varied techniques being applied are also key to understanding the big data arena. The business of data – Take a closer look at the actions connected to data -- the finding, organizing, and analyzing that provide organizations of all sizes with the information they need to compete.


Big Data

Big Data

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  • Author: Viktor Mayer-Schönberger
  • Publisher: Houghton Mifflin Harcourt
  • ISBN: 0544002695
  • Category : Business & Economics
  • Languages : en
  • Pages : 257

A exploration of the latest trend in technology and the impact it will have on the economy, science, and society at large.


Data, Now Bigger and Better!

Data, Now Bigger and Better!

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  • Author: Tom Boellstorff
  • Publisher:
  • ISBN: 9780984201068
  • Category : Social Science
  • Languages : en
  • Pages : 0

Data is too big to be left to the data analysts. Data: Now Bigger and Better brings together researchers whose work is deeply informed by the conceptual frameworks of anthropologyframeworks that are comparative as well as field-based. From kinship to gifts, everything old becomes rich with new insight when the anthropological archive washes over big data. Bringing together anthropology s classic debates and contemporary interventions, the book counters the future-oriented speculation so characteristic of discussions regarding big data. Drawing on the long-standing experience in industry contexts, the contributors also provide analytical provocations that can help reframe some of the most important shifts in technology and society in the first half of the twenty-first century."


Big Data at Work

Big Data at Work

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  • Author: Thomas Davenport
  • Publisher: Harvard Business Review Press
  • ISBN: 1422168174
  • Category : Business & Economics
  • Languages : en
  • Pages : 241

Go ahead, be skeptical about big data. The author was—at first. When the term “big data” first came on the scene, bestselling author Tom Davenport (Competing on Analytics, Analytics at Work) thought it was just another example of technology hype. But his research in the years that followed changed his mind. Now, in clear, conversational language, Davenport explains what big data means—and why everyone in business needs to know about it. Big Data at Work covers all the bases: what big data means from a technical, consumer, and management perspective; what its opportunities and costs are; where it can have real business impact; and which aspects of this hot topic have been oversold. This book will help you understand: • Why big data is important to you and your organization • What technology you need to manage it • How big data could change your job, your company, and your industry • How to hire, rent, or develop the kinds of people who make big data work • The key success factors in implementing any big data project • How big data is leading to a new approach to managing analytics With dozens of company examples, including UPS, GE, Amazon, United Healthcare, Citigroup, and many others, this book will help you seize all opportunities—from improving decisions, products, and services to strengthening customer relationships. It will show you how to put big data to work in your own organization so that you too can harness the power of this ever-evolving new resource.


Big Data

Big Data

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  • Author: James Warren
  • Publisher: Simon and Schuster
  • ISBN: 1638351104
  • Category : Computers
  • Languages : en
  • Pages : 481

Summary Big Data teaches you to build big data systems using an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data. It describes a scalable, easy-to-understand approach to big data systems that can be built and run by a small team. Following a realistic example, this book guides readers through the theory of big data systems, how to implement them in practice, and how to deploy and operate them once they're built. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Book Web-scale applications like social networks, real-time analytics, or e-commerce sites deal with a lot of data, whose volume and velocity exceed the limits of traditional database systems. These applications require architectures built around clusters of machines to store and process data of any size, or speed. Fortunately, scale and simplicity are not mutually exclusive. Big Data teaches you to build big data systems using an architecture designed specifically to capture and analyze web-scale data. This book presents the Lambda Architecture, a scalable, easy-to-understand approach that can be built and run by a small team. You'll explore the theory of big data systems and how to implement them in practice. In addition to discovering a general framework for processing big data, you'll learn specific technologies like Hadoop, Storm, and NoSQL databases. This book requires no previous exposure to large-scale data analysis or NoSQL tools. Familiarity with traditional databases is helpful. What's Inside Introduction to big data systems Real-time processing of web-scale data Tools like Hadoop, Cassandra, and Storm Extensions to traditional database skills About the Authors Nathan Marz is the creator of Apache Storm and the originator of the Lambda Architecture for big data systems. James Warren is an analytics architect with a background in machine learning and scientific computing. Table of Contents A new paradigm for Big Data PART 1 BATCH LAYER Data model for Big Data Data model for Big Data: Illustration Data storage on the batch layer Data storage on the batch layer: Illustration Batch layer Batch layer: Illustration An example batch layer: Architecture and algorithms An example batch layer: Implementation PART 2 SERVING LAYER Serving layer Serving layer: Illustration PART 3 SPEED LAYER Realtime views Realtime views: Illustration Queuing and stream processing Queuing and stream processing: Illustration Micro-batch stream processing Micro-batch stream processing: Illustration Lambda Architecture in depth


Privacy and Big Data

Privacy and Big Data

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  • Author: Terence Craig
  • Publisher: "O'Reilly Media, Inc."
  • ISBN: 1449305008
  • Category : Computers
  • Languages : en
  • Pages : 95

"The players, regulators, and stakeholders"--Cover.


Big Data for Regional Science

Big Data for Regional Science

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  • Author: Laurie A Schintler
  • Publisher: Routledge
  • ISBN: 1351983253
  • Category : Business & Economics
  • Languages : en
  • Pages : 527

Recent technological advancements and other related factors and trends are contributing to the production of an astoundingly large and rapidly accelerating collection of data, or ‘Big Data’. This data now allows us to examine urban and regional phenomena in ways that were previously not possible. Despite the tremendous potential of big data for regional science, its use and application in this context is fraught with issues and challenges. This book brings together leading contributors to present an interdisciplinary, agenda-setting and action-oriented platform for research and practice in the urban and regional community. This book provides a comprehensive, multidisciplinary and cutting-edge perspective on big data for regional science. Chapters contain a collection of research notes contributed by experts from all over the world with a wide array of disciplinary backgrounds. The content is organized along four themes: sources of big data; integration, processing and management of big data; analytics for big data; and, higher level policy and programmatic considerations. As well as concisely and comprehensively synthesising work done to date, the book also considers future challenges and prospects for the use of big data in regional science. Big Data for Regional Science provides a seminal contribution to the field of regional science and will appeal to a broad audience, including those at all levels of academia, industry, and government.


Big Data, Big Dupe

Big Data, Big Dupe

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  • Author: Stephen Few
  • Publisher:
  • ISBN: 9781938377105
  • Category : Computers
  • Languages : en
  • Pages : 0

Argues against the value of big data, suggesting that it is a marketing campaign that distracts from the real and important work of deriving value from data.


Big Data MBA

Big Data MBA

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  • Author: Bill Schmarzo
  • Publisher: John Wiley & Sons
  • ISBN: 1119238846
  • Category : Computers
  • Languages : en
  • Pages : 312

Integrate big data into business to drive competitive advantage and sustainable success Big Data MBA brings insight and expertise to leveraging big data in business so you can harness the power of analytics and gain a true business advantage. Based on a practical framework with supporting methodology and hands-on exercises, this book helps identify where and how big data can help you transform your business. You'll learn how to exploit new sources of customer, product, and operational data, coupled with advanced analytics and data science, to optimize key processes, uncover monetization opportunities, and create new sources of competitive differentiation. The discussion includes guidelines for operationalizing analytics, optimal organizational structure, and using analytic insights throughout your organization's user experience to customers and front-end employees alike. You'll learn to “think like a data scientist” as you build upon the decisions your business is trying to make, the hypotheses you need to test, and the predictions you need to produce. Business stakeholders no longer need to relinquish control of data and analytics to IT. In fact, they must champion the organization's data collection and analysis efforts. This book is a primer on the business approach to analytics, providing the practical understanding you need to convert data into opportunity. Understand where and how to leverage big data Integrate analytics into everyday operations Structure your organization to drive analytic insights Optimize processes, uncover opportunities, and stand out from the rest Help business stakeholders to “think like a data scientist” Understand appropriate business application of different analytic techniques If you want data to transform your business, you need to know how to put it to use. Big Data MBA shows you how to implement big data and analytics to make better decisions.