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Data-centric Living

Data-centric Living
Author: V. Sridhar
Publisher: Taylor & Francis
Total Pages: 305
Release: 2021-11-29
Genre: Social Science
ISBN: 1000483126
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This book explores how data about our everyday online behaviour are collected and how they are processed in various ways by algorithms powered by Artificial Intelligence (AI) and Machine Learning (ML). The book investigates the socioeconomic effects of these technologies, and the evolving regulatory landscape that is aiming to nurture the positive effects of these technology evolutions while at the same time curbing possible negative practices. The volume scrutinizes growing concerns on how algorithmic decisions can sometimes be biased and discriminative; how autonomous systems can possibly disrupt and impact the labour markets, resulting in job losses in several traditional sectors while creating unprecedented opportunities in others; the rapid evolution of social media that can be addictive at times resulting in associated mental health issues; and the way digital Identities are evolving around the world and their impact on provisioning of government services. The book also provides an in-depth understanding of regulations around the world to protect privacy of data subjects in the online world; a glimpse of how data is used as a digital public good in combating Covid pandemic; and how ethical standards in autonomous systems are evolving in the digital world. A timely intervention in this fast-evolving field, this book will be useful for scholars and researchers of digital humanities, business and management, internet studies, data sciences, political studies, urban sociology, law, media and cultural studies, sociology, cultural anthropology, and science and technology studies. It will also be of immense interest to the general readers seeking insights on daily digital lives.

Data and Information Quality

Data and Information Quality
Author: Carlo Batini
Publisher: Springer
Total Pages: 500
Release: 2016-03-23
Genre: Computers
ISBN: 3319241060
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This book provides a systematic and comparative description of the vast number of research issues related to the quality of data and information. It does so by delivering a sound, integrated and comprehensive overview of the state of the art and future development of data and information quality in databases and information systems. To this end, it presents an extensive description of the techniques that constitute the core of data and information quality research, including record linkage (also called object identification), data integration, error localization and correction, and examines the related techniques in a comprehensive and original methodological framework. Quality dimension definitions and adopted models are also analyzed in detail, and differences between the proposed solutions are highlighted and discussed. Furthermore, while systematically describing data and information quality as an autonomous research area, paradigms and influences deriving from other areas, such as probability theory, statistical data analysis, data mining, knowledge representation, and machine learning are also included. Last not least, the book also highlights very practical solutions, such as methodologies, benchmarks for the most effective techniques, case studies, and examples. The book has been written primarily for researchers in the fields of databases and information management or in natural sciences who are interested in investigating properties of data and information that have an impact on the quality of experiments, processes and on real life. The material presented is also sufficiently self-contained for masters or PhD-level courses, and it covers all the fundamentals and topics without the need for other textbooks. Data and information system administrators and practitioners, who deal with systems exposed to data-quality issues and as a result need a systematization of the field and practical methods in the area, will also benefit from the combination of concrete practical approaches with sound theoretical formalisms.

Life and the Law in the Era of Data-Driven Agency

Life and the Law in the Era of Data-Driven Agency
Author: Mireille Hildebrandt
Publisher: Edward Elgar Publishing
Total Pages: 296
Release: 2020-01-31
Genre: Law
ISBN: 1788972007
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This ground-breaking and timely book explores how big data, artificial intelligence and algorithms are creating new types of agency, and the impact that this is having on our lives and the rule of law. Addressing the issues in a thoughtful, cross-disciplinary manner, leading scholars in law, philosophy, computer science and politics examine the ways in which data-driven agency is transforming democratic practices and the meaning of individual choice.

All Data Are Local

All Data Are Local
Author: Yanni Alexander Loukissas
Publisher: MIT Press
Total Pages: 267
Release: 2019-04-30
Genre: Computers
ISBN: 0262039664
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How to analyze data settings rather than data sets, acknowledging the meaning-making power of the local. In our data-driven society, it is too easy to assume the transparency of data. Instead, Yanni Loukissas argues in All Data Are Local, we should approach data sets with an awareness that data are created by humans and their dutiful machines, at a time, in a place, with the instruments at hand, for audiences that are conditioned to receive them. The term data set implies something discrete, complete, and portable, but it is none of those things. Examining a series of data sources important for understanding the state of public life in the United States—Harvard's Arnold Arboretum, the Digital Public Library of America, UCLA's Television News Archive, and the real estate marketplace Zillow—Loukissas shows us how to analyze data settings rather than data sets. Loukissas sets out six principles: all data are local; data have complex attachments to place; data are collected from heterogeneous sources; data and algorithms are inextricably entangled; interfaces recontextualize data; and data are indexes to local knowledge. He then provides a set of practical guidelines to follow. To make his argument, Loukissas employs a combination of qualitative research on data cultures and exploratory data visualizations. Rebutting the “myth of digital universalism,” Loukissas reminds us of the meaning-making power of the local.

Data Driven: Harnessing Data and AI to Reinvent Customer Engagement

Data Driven: Harnessing Data and AI to Reinvent Customer Engagement
Author: Tom Chavez
Publisher: McGraw Hill Professional
Total Pages: 272
Release: 2018-10-05
Genre: Business & Economics
ISBN: 1260441547
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Axiom Business Book Award Silver Medalist in Business Technology The indispensable guide to data-powered marketing from the team behind the data management platform that helps fuel Salesforce―the #1 customer relationship management (CRM) company in the world A tectonic shift in the practice of marketing is underway. Digital technology, social media, and e-commerce have radically changed the way consumers access information, order products, and shop for services. Using the latest technologies―cloud, mobile, social, internet of things (IoT), and artificial intelligence (AI)―we have more data about consumers and their needs, wants, and affinities than ever before. Data Driven will show you how to: ●Target and delight your customers with unprecedented accuracy and success●Bring customers closer to your brand and inspire them to engage, purchase, and remain loyal●Capture, organize, and analyze data from every source and activate it across every channel●Create a data-powered marketing strategy that can be customized for any audience●Serve individual consumers with highly personalized interactions●Deliver better customer service for the best customer experience●Improve your products and optimize your operating systems●Use AI and IoT to predict the future direction of markets You’ll discover the three principles for building a successful data strategy and the five sources of data-driven power. You’ll see how top companies put these data-driven strategies into action: how Pandora used second- and third-hand data to learn more about its listeners; how Georgia-Pacific moved from scarcity to abundance in the data sphere; and how Dunkin’ Brands leveraged CRM data as a force multiplier for customer engagement. And if you’re wondering what the future holds, you’ll receive seven forecasts to better prepare you for what may come next. Sure to be a classic, Data Driven is a practical road map to the modern marketing landscape and a toolkit for success in the face of changes already underway and still to come.

Data Stream Management

Data Stream Management
Author: Minos Garofalakis
Publisher: Springer
Total Pages: 537
Release: 2016-07-11
Genre: Computers
ISBN: 354028608X
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This volume focuses on the theory and practice of data stream management, and the novel challenges this emerging domain poses for data-management algorithms, systems, and applications. The collection of chapters, contributed by authorities in the field, offers a comprehensive introduction to both the algorithmic/theoretical foundations of data streams, as well as the streaming systems and applications built in different domains. A short introductory chapter provides a brief summary of some basic data streaming concepts and models, and discusses the key elements of a generic stream query processing architecture. Subsequently, Part I focuses on basic streaming algorithms for some key analytics functions (e.g., quantiles, norms, join aggregates, heavy hitters) over streaming data. Part II then examines important techniques for basic stream mining tasks (e.g., clustering, classification, frequent itemsets). Part III discusses a number of advanced topics on stream processing algorithms, and Part IV focuses on system and language aspects of data stream processing with surveys of influential system prototypes and language designs. Part V then presents some representative applications of streaming techniques in different domains (e.g., network management, financial analytics). Finally, the volume concludes with an overview of current data streaming products and new application domains (e.g. cloud computing, big data analytics, and complex event processing), and a discussion of future directions in this exciting field. The book provides a comprehensive overview of core concepts and technological foundations, as well as various systems and applications, and is of particular interest to students, lecturers and researchers in the area of data stream management.

Driven by Data

Driven by Data
Author: Paul Bambrick-Santoyo
Publisher: John Wiley & Sons
Total Pages: 298
Release: 2010-04-12
Genre: Education
ISBN: 0470548746
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Offers a practical guide for improving schools dramatically that will enable all students from all backgrounds to achieve at high levels. Includes assessment forms, an index, and a DVD.

Data-Centric Biology

Data-Centric Biology
Author: Sabina Leonelli
Publisher: University of Chicago Press
Total Pages: 282
Release: 2016-11-18
Genre: Science
ISBN: 022641650X
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In recent decades, there has been a major shift in the way researchers process and understand scientific data. Digital access to data has revolutionized ways of doing science in the biological and biomedical fields, leading to a data-intensive approach to research that uses innovative methods to produce, store, distribute, and interpret huge amounts of data. In Data-Centric Biology, Sabina Leonelli probes the implications of these advancements and confronts the questions they pose. Are we witnessing the rise of an entirely new scientific epistemology? If so, how does that alter the way we study and understand life—including ourselves? Leonelli is the first scholar to use a study of contemporary data-intensive science to provide a philosophical analysis of the epistemology of data. In analyzing the rise, internal dynamics, and potential impact of data-centric biology, she draws on scholarship across diverse fields of science and the humanities—as well as her own original empirical material—to pinpoint the conditions under which digitally available data can further our understanding of life. Bridging the divide between historians, sociologists, and philosophers of science, Data-Centric Biology offers a nuanced account of an issue that is of fundamental importance to our understanding of contemporary scientific practices.

DATA CENTRIC.NET,

DATA CENTRIC.NET,
Author: Jacob Hammer Pederson
Publisher: Apress
Total Pages: 822
Release: 2001-12-23
Genre: Science
ISBN: 9781861005922
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The development of the .NET Framework, with the associated release of the C# programming language, is set to stimulate a new wave of application development. This book aims to provide the information needed to develop powerful data-centric applications using C#. To do this it covers the new features of ADO.NET that deliver efficient data access and manipulation, and the XML handling capabilities of the .NET Framework. Accepting that data-centric applications will utilize a variety of sources and inputs, it also looks at additional topics such as using ADO with C#, Messaging Services, and utililizing the Registry and Active Directory. This information is put into context within a number of case studies including one showing how to migrate an application from Visual Basic 6 to C#.

Big Data

Big Data
Author: Viktor Mayer-Schönberger
Publisher: Houghton Mifflin Harcourt
Total Pages: 257
Release: 2013
Genre: Business & Economics
ISBN: 0544002695
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A exploration of the latest trend in technology and the impact it will have on the economy, science, and society at large.