Download or read book Framing Big Data written by Maria Cristina Paganoni and published by Springer. This book was released on 2019-07-03 with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses big data as a socio-technical construct with huge potential for innovation in key sectors such as healthcare, government and business. Big data and its increasingly widespread use in such influential spheres can generate ethically controversial decisions, including questions surrounding privacy, consent and accountability. This book attempts to unpack the epistemological implications of the term ‘big data’, as well as the opportunities and responsibilities which come with it. The author analyses the linguistic texture of the big data narrative in the news media, in healthcare and in EU law on data protection, in order to contribute to its understanding from the critical perspective of language studies. The result is a study which will be of interest to students and scholars working in the digital humanities, corpus linguistics, and discourse studies.
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
Download or read book Frank Kane s Taming Big Data with Apache Spark and Python written by Frank Kane and published by Packt Publishing Ltd. This book was released on 2017-06-30 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: Frank Kane's hands-on Spark training course, based on his bestselling Taming Big Data with Apache Spark and Python video, now available in a book. Understand and analyze large data sets using Spark on a single system or on a cluster. About This Book Understand how Spark can be distributed across computing clusters Develop and run Spark jobs efficiently using Python A hands-on tutorial by Frank Kane with over 15 real-world examples teaching you Big Data processing with Spark Who This Book Is For If you are a data scientist or data analyst who wants to learn Big Data processing using Apache Spark and Python, this book is for you. If you have some programming experience in Python, and want to learn how to process large amounts of data using Apache Spark, Frank Kane's Taming Big Data with Apache Spark and Python will also help you. What You Will Learn Find out how you can identify Big Data problems as Spark problems Install and run Apache Spark on your computer or on a cluster Analyze large data sets across many CPUs using Spark's Resilient Distributed Datasets Implement machine learning on Spark using the MLlib library Process continuous streams of data in real time using the Spark streaming module Perform complex network analysis using Spark's GraphX library Use Amazon's Elastic MapReduce service to run your Spark jobs on a cluster In Detail Frank Kane's Taming Big Data with Apache Spark and Python is your companion to learning Apache Spark in a hands-on manner. Frank will start you off by teaching you how to set up Spark on a single system or on a cluster, and you'll soon move on to analyzing large data sets using Spark RDD, and developing and running effective Spark jobs quickly using Python. Apache Spark has emerged as the next big thing in the Big Data domain – quickly rising from an ascending technology to an established superstar in just a matter of years. Spark allows you to quickly extract actionable insights from large amounts of data, on a real-time basis, making it an essential tool in many modern businesses. Frank has packed this book with over 15 interactive, fun-filled examples relevant to the real world, and he will empower you to understand the Spark ecosystem and implement production-grade real-time Spark projects with ease. Style and approach Frank Kane's Taming Big Data with Apache Spark and Python is a hands-on tutorial with over 15 real-world examples carefully explained by Frank in a step-by-step manner. The examples vary in complexity, and you can move through them at your own pace.
Download or read book Framers written by Kenneth Cukier and published by W H Allen. This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Financial Times and Economist Book of the Year 'Wonderfully stimulating... will teach you to see around corners' - TIM HARFORD 'A paean to cognitive agility and the elasticity of the imagination' - ECONOMIST 'Captivating... will transform the way you think' MARISSA KING, PROFESSOR AT YALE SCHOOL OF MANAGEMENT The power of mental models to make better decisions We're often told that humans make bad decisions and that more data is better. But this is backwards: people are good at decisions precisely because we use mental models and can envision new realities outside of data. Great outcomes don't depend so much on the final moment of choosing but on generating better alternatives to choose between. That's framing. It's a cognitive muscle we can strengthen to improve our lives, work and future -- to meet this historical moment. Framers shows how.
Download or read book Thinking Big Data in Geography written by Jim Thatcher and published by U of Nebraska Press. This book was released on 2018-04-01 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intro -- Title Page -- Copyright Page -- Contents -- List of Illustrations -- List of Tables -- Introduction -- Part 1 -- 1. Toward Critical Data Studies -- 2. Big Data ... Why (Oh Why?) This Computational Social Science? -- Part 2 -- 3. Smaller and Slower Data in an Era of Big Data -- 4. Reflexivity, Positionality, and Rigor in the Context of Big Data Research -- Part 3 -- 5. A Hybrid Approach to Geotweets -- 6. Geosocial Footprints and Geoprivacy Concerns -- 7. Foursquare in the City of Fountains -- Part 4 -- 8. Big City, Big Data -- 9. Framing Digital Exclusion in Technologically Mediated Urban Spaces -- Part 5 -- 10. Bringing the Big Data of Climate Change Down to Human Scale -- 11. Synergizing Geoweb and Digital Humanitarian Research -- Part 6 -- 12. Rethinking the Geoweb and Big Data -- Bibliography -- List of Contributors -- Index -- About Jim Thatcher -- About Josef Eckert -- About Andrew Shears
Download or read book Too Big to Ignore written by Phil Simon and published by John Wiley & Sons. This book was released on 2013-03-05 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
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 Martin Hand and published by Emerald Group Publishing. This book was released on 2014-11-07 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines and engages with the ambivalence of digitization, illuminating the diverse ways in which researchers approach, negotiate, understand and interpret objects and practices of digital research.
Download or read book Frame Theory in Data Science written by Zhihua Zhang and published by Springer Nature. This book was released on with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Big Data written by Fei Hu and published by CRC Press. This book was released on 2016-04-27 with total page 449 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although there are already some books published on Big Data, most of them only cover basic concepts and society impacts and ignore the internal implementation details-making them unsuitable to R&D people. To fill such a need, Big Data: Storage, Sharing, and Security examines Big Data management from an R&D perspective. It covers the 3S desi
Download or read book Introduction to Data Science written by Rafael A. Irizarry and published by CRC Press. This book was released on 2019-11-20 with total page 794 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Data Science: Data Analysis and Prediction Algorithms with R introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression, and machine learning. It also helps you develop skills such as R programming, data wrangling, data visualization, predictive algorithm building, file organization with UNIX/Linux shell, version control with Git and GitHub, and reproducible document preparation. This book is a textbook for a first course in data science. No previous knowledge of R is necessary, although some experience with programming may be helpful. The book is divided into six parts: R, data visualization, statistics with R, data wrangling, machine learning, and productivity tools. Each part has several chapters meant to be presented as one lecture. The author uses motivating case studies that realistically mimic a data scientist’s experience. He starts by asking specific questions and answers these through data analysis so concepts are learned as a means to answering the questions. Examples of the case studies included are: US murder rates by state, self-reported student heights, trends in world health and economics, the impact of vaccines on infectious disease rates, the financial crisis of 2007-2008, election forecasting, building a baseball team, image processing of hand-written digits, and movie recommendation systems. The statistical concepts used to answer the case study questions are only briefly introduced, so complementing with a probability and statistics textbook is highly recommended for in-depth understanding of these concepts. If you read and understand the chapters and complete the exercises, you will be prepared to learn the more advanced concepts and skills needed to become an expert.
Download or read book Thick Big Data written by Dariusz Jemielniak and published by Oxford University Press. This book was released on 2020-03-25 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: The social sciences are becoming datafied. The questions once considered the domain of sociologists are now answered by data scientists operating on large datasets and breaking with methodological tradition, for better or worse. The traditional social sciences, such as sociology or anthropology, are under the double threat of becoming marginalized or even irrelevant, both from new methods of research which require more computational skills and from increasing competition from the corporate world which gains an additional advantage based on data access. However, unlike data scientists, sociologists and anthropologists have a long history of doing qualitative research. The more quantified datasets we have, the more difficult it is to interpret them without adding layers of qualitative interpretation. Big Data therefore needs Thick Data. This book presents the available arsenal of new methods and tools for studying society both quantitatively and qualitatively, opening ground for the social sciences to take the lead in analysing digital behaviour. It shows that Big Data can and should be supplemented and interpreted through thick data as well as cultural analysis. Thick Big Data is critically important for students and researchers in the social sciences to understand the possibilities of digital analysis, both in the quantitative and qualitative area, and to successfully build mixed-methods approaches.
Download or read book Learning to Live with Datafication written by Luci Pangrazio and published by Routledge. This book was released on 2022-03-13 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: As digital technologies play a key role across all aspects of our societies and in everyday life, teaching students about data is becoming increasingly important in schools and universities around the world. Bringing together international case studies of innovative responses to datafication, this book sets an agenda for how teachers, students and policy makers can best understand what kind of educational intervention works and why. Learning to Live with Datafication is unique in its focus on educational responses to datafication as well as critical analysis. Through case studies grounded in empirical research and practice, the book explores the dimensions of datafication from diverse perspectives that bring in a range of cultural aspects. It examines how educators conceptualise the social implications of datafication and what is at stake for learners and citizens as educational institutions try to define what datafication will mean for the next generation. Written by international leaders in this emerging field, this book will be of interest to teacher educators, researchers and post graduate students in education who have an interest in datafication and data literacies.
Download or read book Doing News Framing Analysis II written by Paul D'Angelo and published by Routledge. This book was released on 2018-05-11 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents original, ‘big picture’ perspectives on news framing. Each chapter in this volume will feature an individual or team of framing analysts who take a reflective look at their own empirical work. The editors' goals are to identify the influences that determine the use of different theoretical and methodological approaches, and to provide interpretive guides to news framing scholars regarding what news frames are, how they can be observed in news texts, and how framing effects are uncovered and substantiated in cultural, group, and individual sites. Doing News Framing Analysis II will continue the work of its predecessor by giving talented framing scholars the space to write about their work and bring readers closer to the framing research project. Chapter 9 of this book is freely available as a downloadable Open Access PDF under a Creative Commons Attribution-Non Commercial-No Derivatives 4.0 license available at http://www.taylorfrancis.com.
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 Enterprise Big Data Engineering Analytics and Management written by Atzmueller, Martin and published by IGI Global. This book was released on 2016-06-01 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: The significance of big data can be observed in any decision-making process as it is often used for forecasting and predictive analytics. Additionally, big data can be used to build a holistic view of an enterprise through a collection and analysis of large data sets retrospectively. As the data deluge deepens, new methods for analyzing, comprehending, and making use of big data become necessary. Enterprise Big Data Engineering, Analytics, and Management presents novel methodologies and practical approaches to engineering, managing, and analyzing large-scale data sets with a focus on enterprise applications and implementation. Featuring essential big data concepts including data mining, artificial intelligence, and information extraction, this publication provides a platform for retargeting the current research available in the field. Data analysts, IT professionals, researchers, and graduate-level students will find the timely research presented in this publication essential to furthering their knowledge in the field.
Download or read book Global Inequalities Polarization written by M. Mustafa Erdoğdu and published by IJOPEC PUBLICATION. This book was released on 2020-10-10 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt: Inequalities are increasing across the world and living conditions are very unequal between different parts of the world. Some people can live healthy, rich, and happy lives while others continue to live in poor health, poverty, and grief. Inequalities have greatly strengthened the economic and political power of those people at the top. This volume is titled “Global Inequalities and Polarization” and contains eight selected articles that approach inequality and polarization from different angles.
