Data Selves
Data Selves

Author: Deborah Lupton

Publisher: Polity

Published: 2019-11-25

Total Pages: 208

ISBN-13: 9781509536412

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As people use self-tracking devices and other digital technologies, they generate increasing quantities of personal information online. These data have many benefits, but they can also be accessed and exploited by third parties. In Data Selves, Deborah Lupton develops a fresh and intriguing perspective on how people make sense of and use their personal data, and what they know about others who use this information. Drawing on feminist new materialism theory and the anthropology of material culture, she acknowledges the importance of paying attention to practices, affects, sensory and other embodied experiences, as well as discourses, imaginaries and ideas in identifying the ways in which people make and enact data, and data make and enact people. Arguing that personal data are more-than-human phenomena, invested with diverse forms of vitalities, Lupton reveals significant implications for data futures, politics and ethics. Using rich examples from popular culture and empirical research, this book illustrates the power of data imaginaries, materializations and affects. Lupton's novel approach to understanding personal data will be of interest to students and scholars in media and cultural studies, sociology, anthropology, surveillance studies, and science and technology studies.

We Are Data
We Are Data

Author: John Cheney-Lippold

Publisher: NYU Press

Published: 2017-05-02

Total Pages: 313

ISBN-13: 1479802441

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What identity means in an algorithmic age: how it works, how our lives are controlled by it, and how we can resist it Algorithms are everywhere, organizing the near limitless data that exists in our world. Derived from our every search, like, click, and purchase, algorithms determine the news we get, the ads we see, the information accessible to us and even who our friends are. These complex configurations not only form knowledge and social relationships in the digital and physical world, but also determine who we are and who we can be, both on and offline. Algorithms create and recreate us, using our data to assign and reassign our gender, race, sexuality, and citizenship status. They can recognize us as celebrities or mark us as terrorists. In this era of ubiquitous surveillance, contemporary data collection entails more than gathering information about us. Entities like Google, Facebook, and the NSA also decide what that information means, constructing our worlds and the identities we inhabit in the process. We have little control over who we algorithmically are. Our identities are made useful not for us—but for someone else. Through a series of entertaining and engaging examples, John Cheney-Lippold draws on the social constructions of identity to advance a new understanding of our algorithmic identities. We Are Data will educate and inspire readers who want to wrest back some freedom in our increasingly surveilled and algorithmically-constructed world.

The Self-Service Data Roadmap
The Self-Service Data Roadmap

Author: Sandeep Uttamchandani

Publisher: "O'Reilly Media, Inc."

Published: 2020-09-10

Total Pages: 297

ISBN-13: 1492075205

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Data-driven insights are a key competitive advantage for any industry today, but deriving insights from raw data can still take days or weeks. Most organizations can’t scale data science teams fast enough to keep up with the growing amounts of data to transform. What’s the answer? Self-service data. With this practical book, data engineers, data scientists, and team managers will learn how to build a self-service data science platform that helps anyone in your organization extract insights from data. Sandeep Uttamchandani provides a scorecard to track and address bottlenecks that slow down time to insight across data discovery, transformation, processing, and production. This book bridges the gap between data scientists bottlenecked by engineering realities and data engineers unclear about ways to make self-service work. Build a self-service portal to support data discovery, quality, lineage, and governance Select the best approach for each self-service capability using open source cloud technologies Tailor self-service for the people, processes, and technology maturity of your data platform Implement capabilities to democratize data and reduce time to insight Scale your self-service portal to support a large number of users within your organization

Dear Data
Dear Data

Author: Giorgia Lupi

Publisher: Chronicle Books

Published: 2016-09-13

Total Pages: 304

ISBN-13: 1616895462

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Equal parts mail art, data visualization, and affectionate correspondence, Dear Data celebrates "the infinitesimal, incomplete, imperfect, yet exquisitely human details of life," in the words of Maria Popova (Brain Pickings), who introduces this charming and graphically powerful book. For one year, Giorgia Lupi, an Italian living in New York, and Stefanie Posavec, an American in London, mapped the particulars of their daily lives as a series of hand-drawn postcards they exchanged via mail weekly—small portraits as full of emotion as they are data, both mundane and magical. Dear Data reproduces in pinpoint detail the full year's set of cards, front and back, providing a remarkable portrait of two artists connected by their attention to the details of their lives—including complaints, distractions, phone addictions, physical contact, and desires. These details illuminate the lives of two remarkable young women and also inspire us to map our own lives, including specific suggestions on what data to draw and how. A captivating and unique book for designers, artists, correspondents, friends, and lovers everywhere.

The Quantified Self
The Quantified Self

Author: Deborah Lupton

Publisher: John Wiley & Sons

Published: 2016-09-07

Total Pages: 240

ISBN-13: 1509500634

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With the advent of digital devices and software, self-tracking practices have gained new adherents and have spread into a wide array of social domains. The Quantified Self movement has emerged to promote 'self-knowledge through numbers'. In this groundbreaking book Deborah Lupton critically analyses the social, cultural and political dimensions of contemporary self-tracking and identifies the concepts of selfhood and human embodiment and the value of the data that underpin them. The book incorporates discussion of the consolations and frustrations of self-tracking, as well as about the proliferating ways in which people's personal data are now used beyond their private rationales. Lupton outlines how the information that is generated through self-tracking is taken up and repurposed for commercial, governmental, managerial and research purposes. In the relationship between personal data practices and big data politics, the implications of self-tracking are becoming ever more crucial.

Data Mesh
Data Mesh

Author: Zhamak Dehghani

Publisher: "O'Reilly Media, Inc."

Published: 2022-03-08

Total Pages: 387

ISBN-13: 1492092363

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Many enterprises are investing in a next-generation data lake, hoping to democratize data at scale to provide business insights and ultimately make automated intelligent decisions. In this practical book, author Zhamak Dehghani reveals that, despite the time, money, and effort poured into them, data warehouses and data lakes fail when applied at the scale and speed of today's organizations. A distributed data mesh is a better choice. Dehghani guides architects, technical leaders, and decision makers on their journey from monolithic big data architecture to a sociotechnical paradigm that draws from modern distributed architecture. A data mesh considers domains as a first-class concern, applies platform thinking to create self-serve data infrastructure, treats data as a product, and introduces a federated and computational model of data governance. This book shows you why and how. Examine the current data landscape from the perspective of business and organizational needs, environmental challenges, and existing architectures Analyze the landscape's underlying characteristics and failure modes Get a complete introduction to data mesh principles and its constituents Learn how to design a data mesh architecture Move beyond a monolithic data lake to a distributed data mesh.

Self-Tracking
Self-Tracking

Author: Gina Neff

Publisher: MIT Press

Published: 2016-06-24

Total Pages: 247

ISBN-13: 0262529122

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What happens when people turn their everyday experience into data: an introduction to the essential ideas and key challenges of self-tracking. People keep track. In the eighteenth century, Benjamin Franklin kept charts of time spent and virtues lived up to. Today, people use technology to self-track: hours slept, steps taken, calories consumed, medications administered. Ninety million wearable sensors were shipped in 2014 to help us gather data about our lives. This book examines how people record, analyze, and reflect on this data, looking at the tools they use and the communities they become part of. Gina Neff and Dawn Nafus describe what happens when people turn their everyday experience—in particular, health and wellness-related experience—into data, and offer an introduction to the essential ideas and key challenges of using these technologies. They consider self-tracking as a social and cultural phenomenon, describing not only the use of data as a kind of mirror of the self but also how this enables people to connect to, and learn from, others. Neff and Nafus consider what's at stake: who wants our data and why; the practices of serious self-tracking enthusiasts; the design of commercial self-tracking technology; and how self-tracking can fill gaps in the healthcare system. Today, no one can lead an entirely untracked life. Neff and Nafus show us how to use data in a way that empowers and educates.

Digital Social Research
Digital Social Research

Author: Giuseppe A. Veltri

Publisher: John Wiley & Sons

Published: 2019-10-25

Total Pages: 212

ISBN-13: 1509529330

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To analyse social and behavioural phenomena in our digitalized world, it is necessary to understand the main research opportunities and challenges specific to online and digital data. This book presents an overview of the many techniques that are part of the fundamental toolbox of the digital social scientist. Placing online methods within the wider tradition of social research, Giuseppe Veltri discusses the principles and frameworks that underlie each technique of digital research. This practical guide covers methodological issues such as dealing with different types of digital data, construct validity, representativeness and big data sampling. It looks at different forms of unobtrusive data collection methods (such as web scraping and social media mining) as well as obtrusive methods (including qualitative methods, web surveys and experiments). Special extended attention is given to computational approaches to statistical analysis, text mining and network analysis. Digital Social Research will be a welcome resource for students and researchers across the social sciences and humanities carrying out digital research (or interested in the future of social research).

The Costs of Connection
The Costs of Connection

Author: Nick Couldry

Publisher: Stanford University Press

Published: 2019-08-20

Total Pages: 368

ISBN-13: 1503609758

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Just about any social need is now met with an opportunity to "connect" through digital means. But this convenience is not free—it is purchased with vast amounts of personal data transferred through shadowy backchannels to corporations using it to generate profit. The Costs of Connection uncovers this process, this "data colonialism," and its designs for controlling our lives—our ways of knowing; our means of production; our political participation. Colonialism might seem like a thing of the past, but this book shows that the historic appropriation of land, bodies, and natural resources is mirrored today in this new era of pervasive datafication. Apps, platforms, and smart objects capture and translate our lives into data, and then extract information that is fed into capitalist enterprises and sold back to us. The authors argue that this development foreshadows the creation of a new social order emerging globally—and it must be challenged. Confronting the alarming degree of surveillance already tolerated, they offer a stirring call to decolonize the internet and emancipate our desire for connection.

Self-Service Data Analytics and Governance for Managers
Self-Service Data Analytics and Governance for Managers

Author: Nathan E. Myers

Publisher: John Wiley & Sons

Published: 2021-06-02

Total Pages: 355

ISBN-13: 1119773296

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Project governance, investment governance, and risk governance precepts are woven together in Self-Service Data Analytics and Governance for Managers, equipping managers to structure the inevitable chaos that can result as end-users take matters into their own hands Motivated by the promise of control and efficiency benefits, the widespread adoption of data analytics tools has created a new fast-moving environment of digital transformation in the finance, accounting, and operations world, where entire functions spend their days processing in spreadsheets. With the decentralization of application development as users perform their own analysis on data sets and automate spreadsheet processing without the involvement of IT, governance must be revisited to maintain process control in the new environment. In this book, emergent technologies that have given rise to data analytics and which form the evolving backdrop for digital transformation are introduced and explained, and prominent data analytics tools and capabilities will be demonstrated based on real world scenarios. The authors will provide a much-needed process discovery methodology describing how to survey the processing landscape to identify opportunities to deploy these capabilities. Perhaps most importantly, the authors will digest the mature existing data governance, IT governance, and model governance frameworks, but demonstrate that they do not comprehensively cover the full suite of data analytics builds, leaving a considerable governance gap. This book is meant to fill the gap and provide the reader with a fit-for-purpose and actionable governance framework to protect the value created by analytics deployment at scale. Project governance, investment governance, and risk governance precepts will be woven together to equip managers to structure the inevitable chaos that can result as end-users take matters into their own hands.