Download or read book Big Data Little Data No Data written by Christine L. Borgman and published by MIT Press. This book was released on 2017-02-03 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Big Data written by Viktor Mayer-Schönberger and published by Houghton Mifflin Harcourt. This book was released on 2013 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: A exploration of the latest trend in technology and the impact it will have on the economy, science, and society at large.
Download or read book Big Data written by James Warren and published by Simon and Schuster. This book was released on 2015-04-29 with total page 481 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Small Data written by Martin Lindstrom and published by St. Martin's Press. This book was released on 2016-02-23 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Scholarship in the Digital Age written by Christine L. Borgman and published by MIT Press. This book was released on 2010-08-13 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Big Data in Small Business written by Lund Pedersen, Carsten and published by Edward Elgar Publishing. This book was released on 2021-09-21 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Data Scholarship digital original edition written by Christine L. Borgman and published by MIT Press. This book was released on 2015-04-01 with total page 35 pages. Available in PDF, EPUB and Kindle. Book excerpt: Despite the media hyperbole about “Big Data,” having the right data is usually better than having more data; little data can be just as valuable as big data. This BIT examines the complex set of relationships between data and scholarly research. In it, Christine Borgman, an often-cited authority on scholarly communication, looks at, among other things, knowledge infrastructures, social and technical aspects of digital scholarship, collaboration and community, open access publishing, and open data.
Download or read book Data Smart written by John W. Foreman and published by John Wiley & Sons. This book was released on 2013-10-31 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Small Data Big Disruptions written by Martin Schwirn and published by Red Wheel/Weiser. This book was released on 2021-04-15 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: A method to find and connect the small data clues that show what the future’s big picture will look like. “Strategy decisions are like playing high-stakes blackjack, and scanning is the technique for counting cards. Martin Schwirn isn’t a pro gambler, but an expert in scanning.” —Bill Ralston, cofounder of Strategic Business Insights and author of Scenario Planning Handbook An organization’s future success depends on their decision makers’ ability to anticipate changes and disruptions in the marketplace. But how do you get information about tomorrow today? How can your decisions today account for tomorrow’s uncertainties? Small Data, Big Disruptions presents a tool kit to foresee coming changes: Understand why big data will not help you with understanding tomorrow’s disruptions. The future starts with small data—first. Learn the proven 4-step process to capture small data that help envision the future. See examples of how the process anticipated major disruptions. Implement the process in your organization and learn how to initiate meaningful actions. Small Data, Big Disruptions provides the information you need to anticipate the future, understand tomorrow’s market dynamics, and make the necessary decisions to meet the future on your terms. Small Data, Big Disruptions lets you exploit the period between the moment you could know about emerging disruptions and the moment most everybody will know about it. It’s the difference between being ahead of the curve and struggling to catch up.
Download or read book Big Data Big Analytics written by Michael Minelli and published by John Wiley & Sons. This book was released on 2013-01-22 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unique prospective on the big data analytics phenomenon for both business and IT professionals The availability of Big Data, low-cost commodity hardware and new information management and analytics software has produced a unique moment in the history of business. The convergence of these trends means that we have the capabilities required to analyze astonishing data sets quickly and cost-effectively for the first time in history. These capabilities are neither theoretical nor trivial. They represent a genuine leap forward and a clear opportunity to realize enormous gains in terms of efficiency, productivity, revenue and profitability. The Age of Big Data is here, and these are truly revolutionary times. This timely book looks at cutting-edge companies supporting an exciting new generation of business analytics. Learn more about the trends in big data and how they are impacting the business world (Risk, Marketing, Healthcare, Financial Services, etc.) Explains this new technology and how companies can use them effectively to gather the data that they need and glean critical insights Explores relevant topics such as data privacy, data visualization, unstructured data, crowd sourcing data scientists, cloud computing for big data, and much more.
Download or read book Data Divination written by Pam Baker and published by Course Technology. This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Our world is being transformed by big data. The growth of the Internet and the rapid expansion of mobile communications and related technologies have created a massive flow of data-both structured and unstructured. The availability and use of that data has enormous implications for businesses and for the wider society. Used effectively, big data can drive businesses in the direction of more accurate analyses of vital information. More accurate analyses can lead to more confident decision making-and eventually to greater operational efficiencies, cost reductions, and reduced risk. This book offers detailed instruction in big-data strategy development and implementation, supported by numerous real-world business cases in eight different industries. You will learn what big data is and what tools are available to mine it. Each chapter answers key questions and will give you the skills you need to make your big-data projects succeed. Put big data to work for you and your company today, with Data Divination: Big Data Strategies
Download or read book Big Data Marketing written by Lisa Arthur and published by John Wiley & Sons. This book was released on 2013-10-07 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage big data insights to improve customer experiences and insure business success Many of today's businesses find themselves caught in a snarl of internal data, paralyzed by internal silos, and executing antiquated marketing approaches. As a result, consumers are losing patience, shareholders are clamoring for growth and differentiation, and marketers are left struggling to untangle the massive mess. Big Data Marketing provides a strategic road map for executives who want to clear the chaos and start driving competitive advantage and top line growth. Using real-world examples, non-technical language, additional downloadable resources, and a healthy dose of humor, Big Data Marketing will help you discover the remedy offered by data-driven marketing. Explains how marketers can use data to learn what they need to know Details strategies to drive marketing relevance and Return On Marketing Investment (ROMI) Provides a five-step approach in the journey to a more data-driven marketing organization Author Lisa Arthur, the Chief Marketing Officer for Teradata Applications, the leader in integrated marketing software, meets with thousands of CMOs and marketing professionals annually through public speaking and events Big Data Marketing reveals patterns in your customers' behavior and proven ways to elevate customer experiences. Leverage these insights to insure your business's success.
Download or read book Everydata written by John H. Johnson and published by Routledge. This book was released on 2016-10-14 with total page 247 pages. Available in PDF, EPUB and Kindle. Book excerpt: While everyone is talking about "big data," the truth is that understanding the "little data"--the stats that underlie newspaper headlines, stock reports, weather forecasts, and so on--is what helps you make smarter decisions at work, at home, and in every aspect of your life. The average person consumes approximately 30 gigabytes of data every single day, but has no idea how to interpret it correctly. EVERYDATA explains, through the eyes of an expert economist and statistician, how to decipher the small bytes of data we consume in a day. EVERYDATA is filled with countless examples of people misconstruing data--with results that range from merely frustrating to catastrophic: The space shuttle Challenger exploded in part because the engineers were reviewing a limited sample set. Millions of women avoid caffeine during pregnancy because they interpret correlation as causation. Attorneys faced a $1 billion jury verdict because of outlier data. Each chapter highlights one commonly misunderstood data concept, using both realworld and hypothetical examples from a wide range of topics, including business, politics, advertising, law, engineering, retail, parenting, and more. You'll find the answer to the question--"Now what?"--along with concrete ways you can use this information to immediately start making smarter decisions, today and every day.
Download or read book Big Data Big Dupe written by Stephen Few and published by . This book was released on 2018-02 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Humanizing Big Data written by Colin Strong and published by Kogan Page Publishers. This book was released on 2015-03-03 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data raises more questions than it answers, particularly for those organizations struggling to deal with what has become an overwhelming deluge of data. It can offer marketers more than simple tactical predictive analytics, but organizations need a bigger picture, one that generates some real insight into human behaviour, to drive consumer strategy rather than just better targeting techniques. Humanizing Big Data guides marketing managers, brand managers, strategists and senior executives on how to use big data strategically to redefine customer relationships for better customer engagement and an improved bottom line. Humanizing Big Data provides a detailed understanding of the way to approach and think about the challenges and opportunities of big data, enabling any brand to realize the value of their current and future data assets. First it explores the 'nuts and bolts' of data analytics and the way in which the current big data agenda is in danger of losing credibility by paying insufficient attention to what are often fundamental tenets in any form of analysis. Next it sets out a manifesto for a smart data approach, drawing on an intelligent and big picture view of data analytics that addresses the strategic business challenges that businesses face. Finally it explores the way in which datafication is changing the nature of the relationship between brands and consumers and why this calls for new forms of analytics to support rapidly emerging new business models. After reading this book, any brand should be in a position to make a step change in the value they derive from their data assets.
Download or read book Demystifying Big Data and Machine Learning for Healthcare written by Prashant Natarajan and published by CRC Press. This book was released on 2017-02-15 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: Healthcare transformation requires us to continually look at new and better ways to manage insights – both within and outside the organization today. Increasingly, the ability to glean and operationalize new insights efficiently as a byproduct of an organization’s day-to-day operations is becoming vital to hospitals and health systems ability to survive and prosper. One of the long-standing challenges in healthcare informatics has been the ability to deal with the sheer variety and volume of disparate healthcare data and the increasing need to derive veracity and value out of it. Demystifying Big Data and Machine Learning for Healthcare investigates how healthcare organizations can leverage this tapestry of big data to discover new business value, use cases, and knowledge as well as how big data can be woven into pre-existing business intelligence and analytics efforts. This book focuses on teaching you how to: Develop skills needed to identify and demolish big-data myths Become an expert in separating hype from reality Understand the V’s that matter in healthcare and why Harmonize the 4 C’s across little and big data Choose data fi delity over data quality Learn how to apply the NRF Framework Master applied machine learning for healthcare Conduct a guided tour of learning algorithms Recognize and be prepared for the future of artificial intelligence in healthcare via best practices, feedback loops, and contextually intelligent agents (CIAs) The variety of data in healthcare spans multiple business workflows, formats (structured, un-, and semi-structured), integration at point of care/need, and integration with existing knowledge. In order to deal with these realities, the authors propose new approaches to creating a knowledge-driven learning organization-based on new and existing strategies, methods and technologies. This book will address the long-standing challenges in healthcare informatics and provide pragmatic recommendations on how to deal with them.
Download or read book From Big Data to Big Profits written by Russell Walker and published by Oxford University Press. This book was released on 2015-07-01 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Technological advancements in computing have changed how data is leveraged by businesses to develop, grow, and innovate. In recent years, leading analytical companies have begun to realize the value in their vast holdings of customer data and have found ways to leverage this untapped potential. Now, more firms are following suit and looking to monetize Big Data for big profits. Such changes will have implications for both businesses and consumers in the coming years. In From Big Data to Big Profits, Russell Walker investigates the use of Big Data to stimulate innovations in operational effectiveness and business growth. Walker examines the nature of Big Data and how businesses can use it to create new monetization opportunities. Using case studies of Apple, Netflix, Google, LinkedIn, Zillow, Amazon, and other leaders in the use of Big Data, Walker explores how digital platforms such as mobile apps and social networks are changing the nature of customer interactions and the way Big Data is created and used by companies. Such changes, as Walker points out, will require careful consideration of legal and unspoken business practices as they affect consumer privacy. Companies looking to develop a Big Data strategy will find great value in the SIGMA framework, which he has developed to assess companies for Big Data readiness and provide direction on the steps necessary to get the most from Big Data. Rigorous and meticulous, From Big Data to Big Profits is a valuable resource for students, researchers, and professionals with an interest in Big Data, digital platforms, and analytics
