Author: Evelyn Ruppert
Publisher: MIT Press
ISBN: 1912685868
Category : Social Science
Languages : en
Pages : 257
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Book Description
How EU data practices establish and assign people to categories, and how this matters in enacting--"making up"--Europe as a population and people. What is "Europe" and who are "Europeans"? Data Practices approaches this contemporary political and theoretical question by treating it as a practical problem of counting. Only through the myriad data practices that make up methods such as censuses can EU member states know their national populations, and this in turn is utilized by the EU to understand the population of Europe. But this volume approaches data practices not simply as reflecting populations but as performative in two senses: they simultaneously enact--that is, "make up"--a European population and, by so doing--intentionally or otherwise--also contribute to making up a European people. The book develops a conception of data practices to analyze and interpret findings from collaborative ethnographic multisite fieldwork conducted by an interdisciplinary team of social science researchers as part of a five-year project, Peopling Europe: How Data Make a People. The book focuses on data practices that involve establishing and assigning people to categories and how this matters in enacting Europe as a population and people. Five core chapters explore key categories of people--usual residents, refugees, homeless people, migrants, and ethnic minorities--and how they come into being through specific data practices such as defining, estimating, recalibrating and inferring. Two additional chapters address two key subject positions that data practices produce and require: the data subject and the statistician subject.
Author: James Warren
Publisher: Simon and Schuster
ISBN: 1638351104
Category : Computers
Languages : en
Pages : 498
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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
Author: Jason W. Osborne
Publisher: SAGE
ISBN: 1412988012
Category : Mathematics
Languages : en
Pages : 297
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Book Description
Many researchers jump straight from data collection to data analysis without realizing how analyses and hypothesis tests can go profoundly wrong without clean data. This book provides a clear, step-by-step process of examining and cleaning data in order to decrease error rates and increase both the power and replicability of results. Jason W. Osborne, author of Best Practices in Quantitative Methods (SAGE, 2008) provides easily-implemented suggestions that are research-based and will motivate change in practice by empirically demonstrating, for each topic, the benefits of following best practices and the potential consequences of not following these guidelines. If your goal is to do the best research you can do, draw conclusions that are most likely to be accurate representations of the population(s) you wish to speak about, and report results that are most likely to be replicated by other researchers, then this basic guidebook will be indispensible.
Author: Hadley Wickham
Publisher: "O'Reilly Media, Inc."
ISBN: 1491910364
Category : Computers
Languages : en
Pages : 521
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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: Niall Richard Murphy
Publisher: "O'Reilly Media, Inc."
ISBN: 1491951176
Category :
Languages : en
Pages : 552
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Book Description
The overwhelming majority of a software system’s lifespan is spent in use, not in design or implementation. So, why does conventional wisdom insist that software engineers focus primarily on the design and development of large-scale computing systems? In this collection of essays and articles, key members of Google’s Site Reliability Team explain how and why their commitment to the entire lifecycle has enabled the company to successfully build, deploy, monitor, and maintain some of the largest software systems in the world. You’ll learn the principles and practices that enable Google engineers to make systems more scalable, reliable, and efficient—lessons directly applicable to your organization. This book is divided into four sections: Introduction—Learn what site reliability engineering is and why it differs from conventional IT industry practices Principles—Examine the patterns, behaviors, and areas of concern that influence the work of a site reliability engineer (SRE) Practices—Understand the theory and practice of an SRE’s day-to-day work: building and operating large distributed computing systems Management—Explore Google's best practices for training, communication, and meetings that your organization can use
Author: Jorge Camões
Publisher: New Riders
ISBN: 0134268784
Category : Business & Economics
Languages : en
Pages : 545
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Book Description
Information visualization is a language. Like any language, it can be used for multiple purposes. A poem, a novel, and an essay all share the same language, but each one has its own set of rules. The same is true with information visualization: a product manager, statistician, and graphic designer each approach visualization from different perspectives. Data at Work was written with you, the spreadsheet user, in mind. This book will teach you how to think about and organize data in ways that directly relate to your work, using the skills you already have. In other words, you don’t need to be a graphic designer to create functional, elegant charts: this book will show you how. Although all of the examples in this book were created in Microsoft Excel, this is not a book about how to use Excel. Data at Work will help you to know which type of chart to use and how to format it, regardless of which spreadsheet application you use and whether or not you have any design experience. In this book, you’ll learn how to extract, clean, and transform data; sort data points to identify patterns and detect outliers; and understand how and when to use a variety of data visualizations including bar charts, slope charts, strip charts, scatter plots, bubble charts, boxplots, and more. Because this book is not a manual, it never specifies the steps required to make a chart, but the relevant charts will be available online for you to download, with brief explanations of how they were created.
Author: Athena Vakali
Publisher: IGI Global
ISBN: 1599042282
Category : Computers
Languages : en
Pages : 323
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Book Description
"This book provides an understanding of major issues, current practices and the main ideas in the field of Web data management, helping readers to identify current and emerging issues, as well as future trends. The most important aspects are discussed: Web data mining, content management on the Web, Web applications and Web services"--Provided by publisher.
Author: Piethein Strengholt
Publisher: "O'Reilly Media, Inc."
ISBN: 1492054739
Category : Computers
Languages : en
Pages : 372
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Book Description
As data management and integration continue to evolve rapidly, storing all your data in one place, such as a data warehouse, is no longer scalable. In the very near future, data will need to be distributed and available for several technological solutions. With this practical book, you’ll learnhow to migrate your enterprise from a complex and tightly coupled data landscape to a more flexible architecture ready for the modern world of data consumption. Executives, data architects, analytics teams, and compliance and governance staff will learn how to build a modern scalable data landscape using the Scaled Architecture, which you can introduce incrementally without a large upfront investment. Author Piethein Strengholt provides blueprints, principles, observations, best practices, and patterns to get you up to speed. Examine data management trends, including technological developments, regulatory requirements, and privacy concerns Go deep into the Scaled Architecture and learn how the pieces fit together Explore data governance and data security, master data management, self-service data marketplaces, and the importance of metadata
Author: Giovanna Mascheroni
Publisher: Peter Lang Us
ISBN: 9781433183188
Category : Internet and children
Languages : en
Pages : 202
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Book Description
"What are the consequences of growing up in a datafied world in which social interaction is increasingly dependent on digital media and everyday life is shaped by algorithmic predictions? How is datafication being normalized in children's everyday life? What are the technologies, contexts and relations that enhance children's datafication? What are the meanings of data practices for parents, teachers, and children themselves? These are some of the questions that Mascheroni and Siibak address in Datafied childhoods: Data practices and imaginaries in children's lives. When the data-driven business model emerged twenty years ago, we could not have imagined how pervasive data extraction would have become in the context of everyday life, including the "institutional triangle" of children's lives (the home, the school and the playground). Today, the COVID-19 pandemic has intensified the datafication of everyday life and our reliance on data-relations. Yet, we still know little about the nature, meanings and consequences of the data practices in which children, and the adults around them, engage. This book tries to fill in this gap in two ways. First, drawing on the authors' knowledge of children and media studies and their own research on children's, families' and teachers' interactions with multiple technologies (IoT and IoToys, artificial intelligence, algorithms, robots) in different contexts (home, school and play), it promotes a non-media-centric and child-centered approach. Second, in so doing it encourages further scholarly inquiry into the everyday as the analytical entry point to understand how datafication is transforming parenting, education, childhood and thereby the children"--
Author: Chuck Ballard
Publisher: IBM Redbooks
ISBN: 0738439592
Category : Computers
Languages : en
Pages : 280
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Book Description
This IBM® Redbooks® publication describes how the IBM Big Data Platform provides the integrated capabilities that are required for the adoption of Information Governance in the big data landscape. As organizations embark on new use cases, such as Big Data Exploration, an enhanced 360 view of customers, or Data Warehouse modernization, and absorb ever growing volumes and variety of data with accelerating velocity, the principles and practices of Information Governance become ever more critical to ensure trust in data and help organizations overcome the inherent risks and achieve the wanted value. The introduction of big data changes the information landscape. Data arrives faster than humans can react to it, and issues can quickly escalate into significant events. The variety of data now poses new privacy and security risks. The high volume of information in all places makes it harder to find where these issues, risks, and even useful information to drive new value and revenue are. Information Governance provides an organization with a framework that can align their wanted outcomes with their strategic management principles, the people who can implement those principles, and the architecture and platform that are needed to support the big data use cases. The IBM Big Data Platform, coupled with a framework for Information Governance, provides an approach to build, manage, and gain significant value from the big data landscape.
