Big Data, Little Data, No Data

Author: Christine L. Borgman
Publisher: MIT Press
ISBN: 0262327872
Category : Language Arts & Disciplines
Languages : en
Pages : 411

Book Description
An examination of the uses of data within a changing knowledge infrastructure, offering analysis and case studies from the sciences, social sciences, and humanities. “Big Data” is on the covers of Science, Nature, the Economist, and Wired magazines, on the front pages of the Wall Street Journal and the New York Times. But despite the media hyperbole, as Christine Borgman points out in this examination of data and scholarly research, having the right data is usually better than having more data; little data can be just as valuable as big data. In many cases, there are no data—because relevant data don't exist, cannot be found, or are not available. Moreover, data sharing is difficult, incentives to do so are minimal, and data practices vary widely across disciplines. Borgman, an often-cited authority on scholarly communication, argues that data have no value or meaning in isolation; they exist within a knowledge infrastructure—an ecology of people, practices, technologies, institutions, material objects, and relationships. After laying out the premises of her investigation—six “provocations” meant to inspire discussion about the uses of data in scholarship—Borgman offers case studies of data practices in the sciences, the social sciences, and the humanities, and then considers the implications of her findings for scholarly practice and research policy. To manage and exploit data over the long term, Borgman argues, requires massive investment in knowledge infrastructures; at stake is the future of scholarship.

Big Data

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

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

Big Data in Small Business

Author: Lund Pedersen, Carsten
Publisher: Edward Elgar Publishing
ISBN: 1839100168
Category : Business & Economics
Languages : en
Pages : 272

Book Description
This important book considers the ways in which small and medium-sized enterprises (SMEs) can thrive in the age of big data. To address this central issue from multiple viewpoints, the editors introduce a collection of experiences, insights, and guidelines from a variety of expert researchers, each of whom provides a piece to solve this puzzle.

Too Big to Ignore

Author: Phil Simon
Publisher: John Wiley & Sons
ISBN: 1118641868
Category : Business & Economics
Languages : en
Pages : 256

Book Description
Residents in Boston, Massachusetts are automatically reporting potholes and road hazards via their smartphones. Progressive Insurance tracks real-time customer driving patterns and uses that information to offer rates truly commensurate with individual safety. Google accurately predicts local flu outbreaks based upon thousands of user search queries. Amazon provides remarkably insightful, relevant, and timely product recommendations to its hundreds of millions of customers. Quantcast lets companies target precise audiences and key demographics throughout the Web. NASA runs contests via gamification site TopCoder, awarding prizes to those with the most innovative and cost-effective solutions to its problems. Explorys offers penetrating and previously unknown insights into healthcare behavior. How do these organizations and municipalities do it? Technology is certainly a big part, but in each case the answer lies deeper than that. Individuals at these organizations have realized that they don't have to be Nate Silver to reap massive benefits from today's new and emerging types of data. And each of these organizations has embraced Big Data, allowing them to make astute and otherwise impossible observations, actions, and predictions. It's time to start thinking big. In Too Big to Ignore, recognized technology expert and award-winning author Phil Simon explores an unassailably important trend: Big Data, the massive amounts, new types, and multifaceted sources of information streaming at us faster than ever. Never before have we seen data with the volume, velocity, and variety of today. Big Data is no temporary blip of fad. In fact, it is only going to intensify in the coming years, and its ramifications for the future of business are impossible to overstate. Too Big to Ignore explains why Big Data is a big deal. Simon provides commonsense, jargon-free advice for people and organizations looking to understand and leverage Big Data. Rife with case studies, examples, analysis, and quotes from real-world Big Data practitioners, the book is required reading for chief executives, company owners, industry leaders, and business professionals.

Big Data

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

Book Description
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

Scholarship in the Digital Age

Author: Christine L. Borgman
Publisher: MIT Press
ISBN: 0262250667
Category : Computers
Languages : en
Pages : 363

Book Description
An exploration of the technical, social, legal, and economic aspects of the scholarly infrastructure needed to support research activities in all fields in the twenty-first century. Scholars in all fields now have access to an unprecedented wealth of online information, tools, and services. The Internet lies at the core of an information infrastructure for distributed, data-intensive, and collaborative research. Although much attention has been paid to the new technologies making this possible, from digitized books to sensor networks, it is the underlying social and policy changes that will have the most lasting effect on the scholarly enterprise. In Scholarship in the Digital Age, Christine Borgman explores the technical, social, legal, and economic aspects of the kind of infrastructure that we should be building for scholarly research in the twenty-first century. Borgman describes the roles that information technology plays at every stage in the life cycle of a research project and contrasts these new capabilities with the relatively stable system of scholarly communication, which remains based on publishing in journals, books, and conference proceedings. No framework for the impending “data deluge” exists comparable to that for publishing. Analyzing scholarly practices in the sciences, social sciences, and humanities, Borgman compares each discipline's approach to infrastructure issues. In the process, she challenges the many stakeholders in the scholarly infrastructure—scholars, publishers, libraries, funding agencies, and others—to look beyond their own domains to address the interaction of technical, legal, economic, social, political, and disciplinary concerns. Scholarship in the Digital Age will provoke a stimulating conversation among all who depend on a rich and robust scholarly environment.

Big Data, Little Data, No Data

Author: Christine L. Borgman
Publisher: MIT Press
ISBN: 0262529912
Category : Language Arts & Disciplines
Languages : en
Pages : 411

Data Smart

Author: John W. Foreman
Publisher: John Wiley & Sons
ISBN: 1118839862
Category : Business & Economics
Languages : en
Pages : 432

Book Description
Data Science gets thrown around in the press like it'smagic. Major retailers are predicting everything from when theircustomers are pregnant to when they want a new pair of ChuckTaylors. It's a brave new world where seemingly meaningless datacan be transformed into valuable insight to drive smart businessdecisions. But how does one exactly do data science? Do you have to hireone of these priests of the dark arts, the "data scientist," toextract this gold from your data? Nope. Data science is little more than using straight-forward steps toprocess raw data into actionable insight. And in DataSmart, author and data scientist John Foreman will show you howthat's done within the familiar environment of aspreadsheet. Why a spreadsheet? It's comfortable! You get to look at the dataevery step of the way, building confidence as you learn the tricksof the trade. Plus, spreadsheets are a vendor-neutral place tolearn data science without the hype. But don't let the Excel sheets fool you. This is a book forthose serious about learning the analytic techniques, the math andthe magic, behind big data. Each chapter will cover a different technique in aspreadsheet so you can follow along: Mathematical optimization, including non-linear programming andgenetic algorithms Clustering via k-means, spherical k-means, and graphmodularity Data mining in graphs, such as outlier detection Supervised AI through logistic regression, ensemble models, andbag-of-words models Forecasting, seasonal adjustments, and prediction intervalsthrough monte carlo simulation Moving from spreadsheets into the R programming language You get your hands dirty as you work alongside John through eachtechnique. But never fear, the topics are readily applicable andthe author laces humor throughout. You'll even learnwhat a dead squirrel has to do with optimization modeling, whichyou no doubt are dying to know.

Small Data

Author: Martin Lindstrom
Publisher: St. Martin's Press
ISBN: 1466892595
Category : Business & Economics
Languages : en
Pages : 258

Book Description
Martin Lindstrom, a modern-day Sherlock Holmes, harnesses the power of “small data” in his quest to discover the next big thing Hired by the world's leading brands to find out what makes their customers tick, Martin Lindstrom spends 300 nights a year in strangers’ homes, carefully observing every detail in order to uncover their hidden desires, and, ultimately, the clues to a multi-million dollar product. Lindstrom connects the dots in this globetrotting narrative that will enthrall enterprising marketers, as well as anyone with a curiosity about the endless variations of human behavior. You’ll learn... • How a noise reduction headset at 35,000 feet led to the creation of Pepsi’s new trademarked signature sound. • How a worn down sneaker discovered in the home of an 11-year-old German boy led to LEGO’s incredible turnaround. • How a magnet found on a fridge in Siberia resulted in a U.S. supermarket revolution. • How a toy stuffed bear in a girl’s bedroom helped revolutionize a fashion retailer’s 1,000 stores in 20 different countries. • How an ordinary bracelet helped Jenny Craig increase customer loyalty by 159% in less than a year. • How the ergonomic layout of a car dashboard led to the redesign of the Roomba vacuum.

Man vs Big Data

Author: Stewart Cowley
Publisher: Quarto Publishing Group USA
ISBN: 1781317569
Category : Reference
Languages : en
Pages : 176

Book Description
Have you ever wondered how to beat the bookies? How does your computer know you might like this song? Should you be worried about this?... We can’t answer that for you, but Man vs Big Data does explore the numerous ways in which ‘Big Data’ has, sometimes imperceptibly, infiltrated our lives. Everything we do leaves a trail of data behind, from buying something on a credit card, to using a GPS-enabled mobile phone – whether you know it or not, like it or not, Big Data is now a part of modern life. Heralded as the Fourth Industrial Revolution, it is now more crucial than ever to learn about how data is affecting the way we live. Man vs Big Data proves that this topic is one of the most important subjects facing us today and helps you get to grips with what that means for you.