Framing Big Data PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Framing Big Data PDF full book. Access full book title Framing Big Data by Maria Cristina Paganoni. Download full books in PDF and EPUB format.
Author: Maria Cristina Paganoni
Publisher: Springer
ISBN: 3030167887
Category : Language Arts & Disciplines
Languages : en
Pages : 116
Get Book
Book Description
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.
Author: Maria Cristina Paganoni
Publisher: Springer
ISBN: 3030167887
Category : Language Arts & Disciplines
Languages : en
Pages : 116
Get Book
Book Description
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.
Author: Jim Thatcher
Publisher: U of Nebraska Press
ISBN: 1496205375
Category : Science
Languages : en
Pages : 318
Get Book
Book Description
Thinking Big Data in Geography offers a practical state-of-the-field overview of big data as both a means and an object of research, with essays from prominent and emerging scholars such as Rob Kitchin, Renee Sieber, and Mark Graham. Part 1 explores how the advent of geoweb technologies and big data sets has influenced some of geography’s major subdisciplines: urban politics and political economy, human-environment interactions, and geographic information sciences. Part 2 addresses how the geographic study of big data has implications for other disciplinary fields, notably the digital humanities and the study of social justice. The volume concludes with theoretical applications of the geoweb and big data as they pertain to society as a whole, examining the ways in which user-generated data come into the world and are complicit in its unfolding. The contributors raise caution regarding the use of spatial big data, citing issues of accuracy, surveillance, and privacy.
Author: Hadley Wickham
Publisher: "O'Reilly Media, Inc."
ISBN: 1491910364
Category : Computers
Languages : en
Pages : 521
Get Book
Book Description
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
Author: Zhihua Zhang
Publisher: Springer Nature
ISBN: 3031494830
Category :
Languages : en
Pages : 262
Get Book
Book Description
Author: Martin Hand
Publisher: Emerald Group Publishing
ISBN: 1784410500
Category : Social Science
Languages : en
Pages : 250
Get Book
Book Description
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.
Author: Ann Rudinow Sætnan
Publisher: Routledge
ISBN: 1351866540
Category : Social Science
Languages : en
Pages : 358
Get Book
Book Description
Big Data, gathered together and re-analysed, can be used to form endless variations of our persons - so-called ‘data doubles’. Whilst never a precise portrayal of who we are, they unarguably contain glimpses of details about us that, when deployed into various routines (such as management, policing and advertising) can affect us in many ways. How are we to deal with Big Data? When is it beneficial to us? When is it harmful? How might we regulate it? Offering careful and critical analyses, this timely volume aims to broaden well-informed, unprejudiced discourse, focusing on: the tenets of Big Data, the politics of governance and regulation; and Big Data practices, performance and resistance. An interdisciplinary volume, The Politics of Big Data will appeal to undergraduate and postgraduate students, as well as postdoctoral and senior researchers interested in fields such as Technology, Politics and Surveillance.
Author: Stephen Few
Publisher:
ISBN: 9781938377105
Category : Computers
Languages : en
Pages : 0
Get Book
Book Description
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.
Author: Kenneth Cukier
Publisher: Penguin
ISBN: 0593182596
Category : Psychology
Languages : en
Pages : 273
Get Book
Book Description
“Cukier and his co-authors have a more ambitious project than Kahneman and Harari. They don’t want to just point out how powerfully we are influenced by our perspectives and prejudices—our frames. They want to show us that these frames are tools, and that we can optimise their use.” —Forbes From pandemics to populism, AI to ISIS, wealth inequity to climate change, humanity faces unprecedented challenges that threaten our very existence. The essential tool that will enable humanity to find the best way foward is defined in Framers by internationally renowned authors Kenneth Cukier, Viktor Mayer-Schönberger, and Francis de Véricourt. To frame is to make a mental model that enables us to make sense of new situations. Frames guide the decisions we make and the results we attain. People have long focused on traits like memory and reasoning, leaving framing all but ignored. But with computers becoming better at some of those cognitive tasks, framing stands out as a critical function—and only humans can do it. This book is the first guide to mastering this human ability. Illustrating their case with compelling examples and the latest research, authors Cukier, Mayer-Schönberger, and de Véricourt examine: · Why advice to “think outside the box” is useless · How Spotify beat Apple by reframing music as an experience · How the #MeToo twitter hashtag reframed the perception of sexual assault · The disaster of framing Covid-19 as equivalent to seasonal flu, and how framing it akin to SARS delivered New Zealand from the pandemic Framers shows how framing is not just a way to improve how we make decisions in the era of algorithms—but why it will be a matter of survival for humanity in a time of societal upheaval and machine prosperity.
Author: Kenneth Cukier
Publisher: W H Allen
ISBN: 9780753555002
Category : Problem solving
Languages : en
Pages : 272
Get Book
Book Description
Author: Benjamin Weissman
Publisher: Apress
ISBN: 1484259858
Category : Computers
Languages : en
Pages : 272
Get Book
Book Description
Use this guide to one of SQL Server 2019’s most impactful features—Big Data Clusters. You will learn about data virtualization and data lakes for this complete artificial intelligence (AI) and machine learning (ML) platform within the SQL Server database engine. You will know how to use Big Data Clusters to combine large volumes of streaming data for analysis along with data stored in a traditional database. For example, you can stream large volumes of data from Apache Spark in real time while executing Transact-SQL queries to bring in relevant additional data from your corporate, SQL Server database. Filled with clear examples and use cases, this book provides everything necessary to get started working with Big Data Clusters in SQL Server 2019. You will learn about the architectural foundations that are made up from Kubernetes, Spark, HDFS, and SQL Server on Linux. You then are shown how to configure and deploy Big Data Clusters in on-premises environments or in the cloud. Next, you are taught about querying. You will learn to write queries in Transact-SQL—taking advantage of skills you have honed for years—and with those queries you will be able to examine and analyze data from a wide variety of sources such as Apache Spark. Through the theoretical foundation provided in this book and easy-to-follow example scripts and notebooks, you will be ready to use and unveil the full potential of SQL Server 2019: combining different types of data spread across widely disparate sources into a single view that is useful for business intelligence and machine learning analysis. What You Will LearnInstall, manage, and troubleshoot Big Data Clusters in cloud or on-premise environments Analyze large volumes of data directly from SQL Server and/or Apache Spark Manage data stored in HDFS from SQL Server as if it were relational data Implement advanced analytics solutions through machine learning and AI Expose different data sources as a single logical source using data virtualization Who This Book Is For Data engineers, data scientists, data architects, and database administrators who want to employ data virtualization and big data analytics in their environments
