Data Capital
Data Capital

Author: Chunlei Tang

Publisher: Springer Nature

Published: 2021-01-31

Total Pages: 376

ISBN-13: 3030601927

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This book defines and develops the concept of data capital. Using an interdisciplinary perspective, this book focuses on the key features of the data economy, systematically presenting the economic aspects of data science. The book (1) introduces an alternative interpretation on economists’ observation of which capital has changed radically since the twentieth century; (2) elaborates on the composition of data capital and it as a factor of production; (3) describes morphological changes in data capital that influence its accumulation and circulation; (4) explains the rise of data capital as an underappreciated cause of phenomena from data sovereign, economic inequality, to stagnating productivity; (5) discusses hopes and challenges for industrial circles, the government and academia when an intangible wealth brought by data (and information or knowledge as well); (6) proposes the development of criteria for measuring regulating data capital in the twenty-first century for regulatory purposes by looking at the prospects for data capital and possible impact on future society. Providing the first a thorough introduction to the theory of data as capital, this book will be useful for those studying economics, data science, and business, as well as those in the financial industry who own, control, or wish to work with data resources.

Building the New Economy
Building the New Economy

Author: Alex Pentland

Publisher: MIT Press

Published: 2021-10-12

Total Pages: 475

ISBN-13: 026254315X

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How to empower people and communities with user-centric data ownership, transparent and accountable algorithms, and secure digital transaction systems. Data is now central to the economy, government, and health systems—so why are data and the AI systems that interpret the data in the hands of so few people? Building the New Economy calls for us to reinvent the ways that data and artificial intelligence are used in civic and government systems. Arguing that we need to think about data as a new type of capital, the authors show that the use of data trusts and distributed ledgers can empower people and communities with user-centric data ownership, transparent and accountable algorithms, machine learning fairness principles and methodologies, and secure digital transaction systems. It’s well known that social media generate disinformation and that mobile phone tracking apps threaten privacy. But these same technologies may also enable the creation of more agile systems in which power and decision-making are distributed among stakeholders rather than concentrated in a few hands. Offering both big ideas and detailed blueprints, the authors describe such key building blocks as data cooperatives, tokenized funding mechanisms, and tradecoin architecture. They also discuss technical issues, including how to build an ecosystem of trusted data, the implementation of digital currencies, and interoperability, and consider the evolution of computational law systems.

Social Classes and Political Order in the Age of Data
Social Classes and Political Order in the Age of Data

Author: Georges Kotrotsios

Publisher: Cambridge Scholars Publishing

Published: 2022-09-28

Total Pages: 178

ISBN-13: 1527589056

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Our lives are changing today, but what is the single most important factor driving these changes? This question is crucial, because attempting to answer it can guide us to an understanding of the processes that are impacting our societies. The answer will, of course, come from the historians of the future, but there is already no doubt that the advent of data is behind a radical shake-up of our way of living. Monetary assets, infrastructure, equipment, and human labor all allow wealth to be created. Data does too, and it is reasonable to consider a new production factor in this regard: data capital. This book argues that this new production factor generates innumerable economic opportunities of a nature unthought of a mere twenty years ago. These opportunities have led to the creation of a new social class composed of two subclasses: data workers and data owners. The emergence of this new class repositions existing classes, including the traditional working class and the capitalist class, creating strong divergences that threaten social cohesion. What can we do to ensure cohesion and the proper functioning of society? The book argues for the establishment of a regulatory framework and the institutions necessary if we are to open data up and, where appropriate, exchange and trade it, all on a global scale. In this regard, the state—today still playing its traditional role of framework setter, and savior when crises loom—can become an active economic player, thus creating wealth for communities.

Market Data Explained
Market Data Explained

Author: Marc Alvarez

Publisher: Elsevier

Published: 2011-04-01

Total Pages: 135

ISBN-13: 0080465781

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Market Data Explained is intended to provide a guide to the universe of data content produced by the global capital markets on a daily basis. Commonly referred to as "market data, the universe of content is very wide and the type of information correspondingly diverse. Jargon and acronyms are very common. As a result, users of marker data typically face difficulty in applying the content in analysis and business applications. This guide provides an independent framework for understanding this diversity and streamlining the process of referring to content and how it relates to today's business environment. The book achieves this goal by providing a consistent frame of reference for users of market data. As such, it is built around the concept of a data model – a single, coherent view of the capital markets independent of any one source, such as an exchange. In particular it delineates clearly between the actual data content and how it is delivered (i.e., realtime data streams versus reference data). It shows how the data relates across the universe of securities (i.e., stocks, bonds, derivatives etc.). In this way it provides a logical framework for understanding how new content can be added over time as the business develops. Special features: 1. Uniqueness – this is the first comprehensive catalog and taxonomy to be made available for a business audience 2. Industry Acceptance – the framework described in this book is implemented as a relational data model in the industry today and used by blue chip multinational firms 3. Comprehensiveness – there are no arbitrary distinctions made based on asset class or data type (the legacy approach). The model presented in this book is fully cross asset and makes no distinction between data types (i.e., realtime versus historical/reference data) or sources 4. Independence – the framework is an independent, objective overview of how the data content integrates to provide a coherent view of the data produced by the global capital markets on a daily and intra-day basis. It provides a logical framework for referring to the content and entities that are so intrinsic to this industry - First and only single, comprehensive desk reference to market data produced by the global capital markets on a daily basis - Provides a comprehensive catalog of the market data and a common structure for navigating the complex content and interrelationships - Provides a common taxonomy and naming conventions that handles the highly varied, geographically and language dependent nature of the content

A Proposal to Improve Country-Level Data on Total Factor Productivity Growth
A Proposal to Improve Country-Level Data on Total Factor Productivity Growth

Author: Andrew Warner

Publisher: International Monetary Fund

Published: 2024-03-22

Total Pages: 39

ISBN-13:

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The assumption behind popular data on national capital stocks, and therefore total factor productivity, is that countries were in a steady state in the first year that investment data became available. This paper argues that this assumption is highly implausible and is necessarily responsible for implausible data on the ratio of capital to output and productivity growth. It is not credible that countries with similar incomes had huge differences in their capital stocks. This paper claims, with evidence, that implausible features of the data can be greatly reduced by using data on electricity usage or national stocks of road vehicles.

Technology Strategy
Technology Strategy

Author: Nigel Walton

Publisher: Bloomsbury Publishing

Published: 2019-09-21

Total Pages: 327

ISBN-13: 1137605359

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This dynamic and beautifully written textbook takes a modern and innovative approach to strategy by placing technology at its heart, bridging the gap between general strategy texts and specialist technology and innovation literature. It addresses the challenges and opportunities presented to organisations by disruptive technological change and takes into account the navigation of uncertain business environments. In addition to examining more established concepts and theories, the text also explores new disruptive business models and non-traditional approaches to strategy development such as effectuation, the Business Model Canvas and prediction logic. This comprehensive and critical approach is supported by a rich assortment of practical examples and cases drawn from different sectors and a range of exciting companies from all over the world, helping students and practitioners to apply theory to practice. This will be an essential core text for modules on technology strategy and innovation at upper undergraduate, postgraduate and MBA levels, and invaluable reading for senior executives and aspiring managers who seek to understand how to implement strategy in a volatile disruptive environment.

Ethnography for a data-saturated world
Ethnography for a data-saturated world

Author: Hannah Knox

Publisher: Manchester University Press

Published: 2018-10-03

Total Pages: 236

ISBN-13: 152612761X

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This edited collection aims to reimagine and extend ethnography for a data-saturated world. The book brings together leading scholars in the social sciences who have been interrogating and collaborating with data scientists working in a range of different settings. The book explores how a repurposed form of ethnography might illuminate the kinds of knowledge that are being produced by data science. It also describes how collaborations between ethnographers and data scientists might lead to new forms of social analysis

Too Smart
Too Smart

Author: Jathan Sadowski

Publisher: MIT Press

Published: 2020-03-24

Total Pages: 253

ISBN-13: 026253858X

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Who benefits from smart technology? Whose interests are served when we trade our personal data for convenience and connectivity? Smart technology is everywhere: smart umbrellas that light up when rain is in the forecast; smart cars that relieve drivers of the drudgery of driving; smart toothbrushes that send your dental hygiene details to the cloud. Nothing is safe from smartification. In Too Smart, Jathan Sadowski looks at the proliferation of smart stuff in our lives and asks whether the tradeoff—exchanging our personal data for convenience and connectivity—is worth it. Who benefits from smart technology? Sadowski explains how data, once the purview of researchers and policy wonks, has become a form of capital. Smart technology, he argues, is driven by the dual imperatives of digital capitalism: extracting data from, and expanding control over, everything and everybody. He looks at three domains colonized by smart technologies' collection and control systems: the smart self, the smart home, and the smart city. The smart self involves more than self-tracking of steps walked and calories burned; it raises questions about what others do with our data and how they direct our behavior—whether or not we want them to. The smart home collects data about our habits that offer business a window into our domestic spaces. And the smart city, where these systems have space to grow, offers military-grade surveillance capabilities to local authorities. Technology gets smart from our data. We may enjoy the conveniences we get in return (the refrigerator says we're out of milk!), but, Sadowski argues, smart technology advances the interests of corporate technocratic power—and will continue to do so unless we demand oversight and ownership of our data.

Qlik Sense: Advanced Data Visualization for Your Organization
Qlik Sense: Advanced Data Visualization for Your Organization

Author: Ferran Garcia Pagans

Publisher: Packt Publishing Ltd

Published: 2017-12-27

Total Pages: 765

ISBN-13: 1788998723

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Perform Interactive Data Analysis with Smarter Visualizations and Support your Enterprise-wide Analytical Needs Key Features Get a practical demonstration of discovering data for sales, human resources, and more using Qlik Sense Create dynamic dashboards for business intelligence and predictive analytics Create and collaborate comprehensive analytical solutions using Rattle and Qlik Sense Book Description Qlik Sense is powerful and creative visual analytics software that allows users to discover data, explore it, and dig out meaningful insights in order to make a profit and make decisions for your business. This course begins by introducing you to the features and functions of the most modern edition of Qlik Sense so you get to grips with the application. The course will teach you how to administer the data architecture in Qlik Sense, enabling you to customize your own Qlik Sense application for your business intelligence needs. It also contains numerous recipes to help you overcome challenging situations while creating fully featured desktop applications in Qlik Sense. It explains how to combine Rattle and Qlik Sense Desktop to apply predictive analytics to your data to develop real-world interactive data applications. The course includes premium content from three of our most popular books: [*] Learning Qlik Sense: The Official Guide Second Edition [*] Qlik Sense Cookbook [*] Predictive Analytics using Rattle and Qlik Sense On completion of this course, you will be self-sufficient in improving your data analysis and will know how to apply predictive analytics to your datasets. Through this course, you will be able to create predictive models and data applications, allowing you to explore your data insights much deeper. What you will learn Build simple visualization models with Rattle and Qlik Sense Desktop Get to grips with the life cycle and new visualization functions of a Qlik Sense application Discover simple ways to examine data and get it ready for analysis Visualize your data with Qlik Sense's engaging and informative graphs Build efficient and responsive Associative Models Optimize Qlik Sense for sales, human resources, and demographic data discovery Explore various tips and tricks of navigation for the Qlik Sense® front end Develop creative extensions for your Qlik Sense® dashboard Who this book is for This course is for anyone who wishes to understand and utilize the various new approaches to business intelligence actively in their business practice. Knowing the basics of business intelligence concepts would be helpful when picking up this course, but is not mandatory.