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Book Synopsis Big Data by : Viktor Mayer-Schönberger
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.
Book Synopsis The Elements of Big Data Value by : Edward Curry
Download or read book The Elements of Big Data Value written by Edward Curry and published by Springer Nature. This book was released on 2021-08-01 with total page 399 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book presents the foundations of the Big Data research and innovation ecosystem and the associated enablers that facilitate delivering value from data for business and society. It provides insights into the key elements for research and innovation, technical architectures, business models, skills, and best practices to support the creation of data-driven solutions and organizations. The book is a compilation of selected high-quality chapters covering best practices, technologies, experiences, and practical recommendations on research and innovation for big data. The contributions are grouped into four parts: · Part I: Ecosystem Elements of Big Data Value focuses on establishing the big data value ecosystem using a holistic approach to make it attractive and valuable to all stakeholders. · Part II: Research and Innovation Elements of Big Data Value details the key technical and capability challenges to be addressed for delivering big data value. · Part III: Business, Policy, and Societal Elements of Big Data Value investigates the need to make more efficient use of big data and understanding that data is an asset that has significant potential for the economy and society. · Part IV: Emerging Elements of Big Data Value explores the critical elements to maximizing the future potential of big data value. Overall, readers are provided with insights which can support them in creating data-driven solutions, organizations, and productive data ecosystems. The material represents the results of a collective effort undertaken by the European data community as part of the Big Data Value Public-Private Partnership (PPP) between the European Commission and the Big Data Value Association (BDVA) to boost data-driven digital transformation.
Book Synopsis Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming Data by : Paul Zikopoulos
Download or read book Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming Data written by Paul Zikopoulos and published by McGraw Hill Professional. This book was released on 2011-10-22 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data represents a new era in data exploration and utilization, and IBM is uniquely positioned to help clients navigate this transformation. This book reveals how IBM is leveraging open source Big Data technology, infused with IBM technologies, to deliver a robust, secure, highly available, enterprise-class Big Data platform. The three defining characteristics of Big Data--volume, variety, and velocity--are discussed. You'll get a primer on Hadoop and how IBM is hardening it for the enterprise, and learn when to leverage IBM InfoSphere BigInsights (Big Data at rest) and IBM InfoSphere Streams (Big Data in motion) technologies. Industry use cases are also included in this practical guide. Learn how IBM hardens Hadoop for enterprise-class scalability and reliability Gain insight into IBM's unique in-motion and at-rest Big Data analytics platform Learn tips and tricks for Big Data use cases and solutions Get a quick Hadoop primer
Book Synopsis R for Data Science by : Hadley Wickham
Download or read book R for Data Science written by Hadley Wickham and published by "O'Reilly Media, Inc.". This book was released on 2016-12-12 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results
Book Synopsis The Rise of Big Data Policing by : Andrew Guthrie Ferguson
Download or read book The Rise of Big Data Policing written by Andrew Guthrie Ferguson and published by NYU Press. This book was released on 2019-11-15 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: Winner, 2018 Law & Legal Studies PROSE Award The consequences of big data and algorithm-driven policing and its impact on law enforcement In a high-tech command center in downtown Los Angeles, a digital map lights up with 911 calls, television monitors track breaking news stories, surveillance cameras sweep the streets, and rows of networked computers link analysts and police officers to a wealth of law enforcement intelligence. This is just a glimpse into a future where software predicts future crimes, algorithms generate virtual “most-wanted” lists, and databanks collect personal and biometric information. The Rise of Big Data Policing introduces the cutting-edge technology that is changing how the police do their jobs and shows why it is more important than ever that citizens understand the far-reaching consequences of big data surveillance as a law enforcement tool. Andrew Guthrie Ferguson reveals how these new technologies —viewed as race-neutral and objective—have been eagerly adopted by police departments hoping to distance themselves from claims of racial bias and unconstitutional practices. After a series of high-profile police shootings and federal investigations into systemic police misconduct, and in an era of law enforcement budget cutbacks, data-driven policing has been billed as a way to “turn the page” on racial bias. But behind the data are real people, and difficult questions remain about racial discrimination and the potential to distort constitutional protections. In this first book on big data policing, Ferguson offers an examination of how new technologies will alter the who, where, when and how we police. These new technologies also offer data-driven methods to improve police accountability and to remedy the underlying socio-economic risk factors that encourage crime. The Rise of Big Data Policing is a must read for anyone concerned with how technology will revolutionize law enforcement and its potential threat to the security, privacy, and constitutional rights of citizens. Read an excerpt and interview with Andrew Guthrie Ferguson in The Economist.
Book Synopsis The Big Data Revolution by : Jason Kolb
Download or read book The Big Data Revolution written by Jason Kolb and published by Createspace Independent Publishing Platform. This book was released on 2013 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We create more data in a day then we did from the dawn of man through 2003 and approximately 90% of all the world's data has been created in the past 2 years. What does this mean to you? In The Big Data Revolution we explore this very question and reveal the data secrets your competitors don't want you to know. Our world is transforming as the data deluge knocks us out of our old ways and into the data driven reality. Some companies are winning by taking advantages of the opportunities in this evolving world while others are falling behind. Pioneers like Amazon, Target, and Google are blazing a trail that we can follow, and in The Big Data Revolution we help you do just that. Big Data promises to give us a world driven by information and solid data, bringing far greater productivity, increased profits, and lower costs; and in The Big Data Revolution we explore those winning strategies and techniques and the tools behind them. Want to learn how companies like Amazon, Target, and IBM use data to gain competitive advantages? Or how Obama used Big Data tools to better utilize his resources? The Big Data Revolution was written for the non-or-only-slightly-technical business person in mind--but in a way that gives you enough meat behind the ideas so that you have a road map that tells you how to get where you want to go. It uses real-world examples and case studies to illustrates the concepts and explore the technology that makes them happen. The Big Data Revolution is comprised of four parts: Part 1: Data Science In Part 1 we first introduce you to the world of data science and analytics. These are the tools companies and governments use to refine their crude data into valuable insights. In this section, we'll look at the magic behind Amazon's success, and see how data is leading towards a near Minority Report future. Part 2: Big Data Data is growing at an exceptional rate, we produce more data now in a day than we did from the dawn of man till 2003. This explosion of data creates many unique struggles as well as opportunities. In this section we'll look at how Obama invested in Big Data during his presidential campaign, and explore how startups are revealing data that saves their clients substantial capital. Part 3: Tools of the trade Data Scientists cannot just look at big data and get value from it, it doesn't matter how good they are. The data is just too big. So companies like IBM and Microsoft build tools that help people make sense of data, and hopefully discover new useful insights from it. The two primary categories of tools you need to be aware of are Business Intelligence and Data Discovery. In this section we explore these broad terms, and show how companies are designing more specialized tools for specific purposes. Part 4: Gazing into the Future In order to position yourself well for what is to come you need to know where we are now and almost more importantly where we are going to be in the near future. In this section we explore the trends that are going to matter as we move forward in this emerging technology industry. Computerized Data Analytics is truly still in its early stages of development, and things are going to change as new innovations come to the forefront. If we are serious about gaining the data advantage, we need to stay ahead of this curve. The Big Data Revolution is your tool to understanding this complex new reality of your world. Get it today and don't miss out on the data driven future. The world is changing. Are you ready?
Book Synopsis ANALYSE DU SENTIMENT DU MARCHÉ AVEC LE BIG DATA by : Marcel Souza
Download or read book ANALYSE DU SENTIMENT DU MARCHÉ AVEC LE BIG DATA written by Marcel Souza and published by Gavea. This book was released on with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt: Analyse du Sentiment du Marché avec le Big Data est un guide essentiel pour les traders, les analystes et les investisseurs qui souhaitent exploiter le pouvoir des données massives pour comprendre et anticiper les mouvements du marché. Grâce à des techniques avancées de traitement et d'analyse des données, ce livre vous permettra de mieux comprendre les émotions et les comportements des acteurs du marché, souvent invisibles dans les données traditionnelles. Découvrez comment le Big Data peut révéler des tendances cachées et offrir des perspectives uniques sur la dynamique des marchés financiers. Ce livre explore en profondeur les différentes méthodes d'analyse du sentiment, y compris l'exploration de données des réseaux sociaux, des forums financiers et d'autres sources en ligne. Il explique comment utiliser ces données pour identifier les signaux d'achat et de vente, évaluer l'impact des événements économiques et politiques sur les marchés et mieux comprendre la psychologie des investisseurs. Que vous soyez un novice ou un expert, ce livre vous fournira les outils nécessaires pour intégrer ces techniques dans votre stratégie de trading. En combinant les concepts traditionnels de l'analyse technique et fondamentale avec des approches basées sur le Big Data, Analyse du Sentiment du Marché avec le Big Data offre une perspective nouvelle et puissante sur la manière de réussir dans le monde complexe des investissements. Vous apprendrez à interpréter les fluctuations des prix, à identifier les opportunités et à prendre des décisions plus informées grâce à l'analyse de millions de points de données en temps réel. Avec des études de cas concrètes et des exemples pratiques, cet ouvrage est une ressource indispensable pour quiconque souhaite maîtriser l'art de l'analyse du sentiment de marché à l'ère du numérique. Plongez dans l'univers du Big Data et transformez votre approche de l'investissement pour maximiser vos rendements tout en minimisant les risques.
Book Synopsis Big Data by : Viktor Mayer-Schönberger
Download or read book Big Data written by Viktor Mayer-Schönberger and published by John Murray Press. This book was released on 2017 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explores the idea of big data, which refers to our new found ability to crunch vast amounts of information, analyze it instantly, and draw profound and surprising conclusions from it.
Download or read book Big Data written by Balamurugan Balusamy and published by John Wiley & Sons. This book was released on 2021-03-15 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn Big Data from the ground up with this complete and up-to-date resource from leaders in the field Big Data: Concepts, Technology, and Architecture delivers a comprehensive treatment of Big Data tools, terminology, and technology perfectly suited to a wide range of business professionals, academic researchers, and students. Beginning with a fulsome overview of what we mean when we say, “Big Data,” the book moves on to discuss every stage of the lifecycle of Big Data. You’ll learn about the creation of structured, unstructured, and semi-structured data, data storage solutions, traditional database solutions like SQL, data processing, data analytics, machine learning, and data mining. You’ll also discover how specific technologies like Apache Hadoop, SQOOP, and Flume work. Big Data also covers the central topic of big data visualization with Tableau, and you’ll learn how to create scatter plots, histograms, bar, line, and pie charts with that software. Accessibly organized, Big Data includes illuminating case studies throughout the material, showing you how the included concepts have been applied in real-world settings. Some of those concepts include: The common challenges facing big data technology and technologists, like data heterogeneity and incompleteness, data volume and velocity, storage limitations, and privacy concerns Relational and non-relational databases, like RDBMS, NoSQL, and NewSQL databases Virtualizing Big Data through encapsulation, partitioning, and isolating, as well as big data server virtualization Apache software, including Hadoop, Cassandra, Avro, Pig, Mahout, Oozie, and Hive The Big Data analytics lifecycle, including business case evaluation, data preparation, extraction, transformation, analysis, and visualization Perfect for data scientists, data engineers, and database managers, Big Data also belongs on the bookshelves of business intelligence analysts who are required to make decisions based on large volumes of information. Executives and managers who lead teams responsible for keeping or understanding large datasets will also benefit from this book.
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.
Book Synopsis Big Data in Education by : Ben Williamson
Download or read book Big Data in Education written by Ben Williamson and published by SAGE. This book was released on 2017-07-24 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data has the power to transform education and educational research. Governments, researchers and commercial companies are only beginning to understand the potential that big data offers in informing policy ideas, contributing to the development of new educational tools and innovative ways of conducting research. This cutting-edge overview explores the current state-of-play, looking at big data and the related topic of computer code to examine the implications for education and schooling for today and the near future. Key topics include: · The role of learning analytics and educational data science in schools · A critical appreciation of code, algorithms and infrastructures · The rise of ‘cognitive classrooms’, and the practical application of computational algorithms to learning environments · Important digital research methods issues for researchers This is essential reading for anyone studying or working in today′s education environment!
Book Synopsis Data Science and Big Data Analytics by : EMC Education Services
Download or read book Data Science and Big Data Analytics written by EMC Education Services and published by John Wiley & Sons. This book was released on 2014-12-19 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software. This book will help you: Become a contributor on a data science team Deploy a structured lifecycle approach to data analytics problems Apply appropriate analytic techniques and tools to analyzing big data Learn how to tell a compelling story with data to drive business action Prepare for EMC Proven Professional Data Science Certification Get started discovering, analyzing, visualizing, and presenting data in a meaningful way today!
Book Synopsis Data Feminism by : Catherine D'Ignazio
Download or read book Data Feminism written by Catherine D'Ignazio and published by MIT Press. This book was released on 2020-03-31 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: A new way of thinking about data science and data ethics that is informed by the ideas of intersectional feminism. Today, data science is a form of power. It has been used to expose injustice, improve health outcomes, and topple governments. But it has also been used to discriminate, police, and surveil. This potential for good, on the one hand, and harm, on the other, makes it essential to ask: Data science by whom? Data science for whom? Data science with whose interests in mind? The narratives around big data and data science are overwhelmingly white, male, and techno-heroic. In Data Feminism, Catherine D'Ignazio and Lauren Klein present a new way of thinking about data science and data ethics—one that is informed by intersectional feminist thought. Illustrating data feminism in action, D'Ignazio and Klein show how challenges to the male/female binary can help challenge other hierarchical (and empirically wrong) classification systems. They explain how, for example, an understanding of emotion can expand our ideas about effective data visualization, and how the concept of invisible labor can expose the significant human efforts required by our automated systems. And they show why the data never, ever “speak for themselves.” Data Feminism offers strategies for data scientists seeking to learn how feminism can help them work toward justice, and for feminists who want to focus their efforts on the growing field of data science. But Data Feminism is about much more than gender. It is about power, about who has it and who doesn't, and about how those differentials of power can be challenged and changed.
Book Synopsis Guide to Big Data Applications by : S. Srinivasan
Download or read book Guide to Big Data Applications written by S. Srinivasan and published by Springer. This book was released on 2017-05-25 with total page 567 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook brings together a variety of approaches to the uses of big data in multiple fields, primarily science, medicine, and business. This single resource features contributions from researchers around the world from a variety of fields, where they share their findings and experience. This book is intended to help spur further innovation in big data. The research is presented in a way that allows readers, regardless of their field of study, to learn from how applications have proven successful and how similar applications could be used in their own field. Contributions stem from researchers in fields such as physics, biology, energy, healthcare, and business. The contributors also discuss important topics such as fraud detection, privacy implications, legal perspectives, and ethical handling of big data.
Download or read book Big Data written by Bernard Marr and published by John Wiley & Sons. This book was released on 2015-01-09 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Convert the promise of big data into real world results There is so much buzz around big data. We all need to know what it is and how it works - that much is obvious. But is a basic understanding of the theory enough to hold your own in strategy meetings? Probably. But what will set you apart from the rest is actually knowing how to USE big data to get solid, real-world business results - and putting that in place to improve performance. Big Data will give you a clear understanding, blueprint, and step-by-step approach to building your own big data strategy. This is a well-needed practical introduction to actually putting the topic into practice. Illustrated with numerous real-world examples from a cross section of companies and organisations, Big Data will take you through the five steps of the SMART model: Start with Strategy, Measure Metrics and Data, Apply Analytics, Report Results, Transform. Discusses how companies need to clearly define what it is they need to know Outlines how companies can collect relevant data and measure the metrics that will help them answer their most important business questions Addresses how the results of big data analytics can be visualised and communicated to ensure key decisions-makers understand them Includes many high-profile case studies from the author's work with some of the world's best known brands
Download or read book The History Manifesto written by Jo Guldi and published by Cambridge University Press. This book was released on 2014-10-02 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: How should historians speak truth to power – and why does it matter? Why is five hundred years better than five months or five years as a planning horizon? And why is history – especially long-term history – so essential to understanding the multiple pasts which gave rise to our conflicted present? The History Manifesto is a call to arms to historians and everyone interested in the role of history in contemporary society. Leading historians Jo Guldi and David Armitage identify a recent shift back to longer-term narratives, following many decades of increasing specialisation, which they argue is vital for the future of historical scholarship and how it is communicated. This provocative and thoughtful book makes an important intervention in the debate about the role of history and the humanities in a digital age. It will provoke discussion among policymakers, activists and entrepreneurs as well as ordinary listeners, viewers, readers, students and teachers. This title is also available as Open Access.
Book Synopsis Designing Data-Intensive Applications by : Martin Kleppmann
Download or read book Designing Data-Intensive Applications written by Martin Kleppmann and published by "O'Reilly Media, Inc.". This book was released on 2017-03-16 with total page 658 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords? In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures
