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(32 publications available)

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    Omni-Channel Retailing
    (Springer Gabler Wiesbaden, 2021) Winters, Amelie
    Amelie Winters investigates omni-channel strategies in retail and provides new insights and important implications for researchers and managers based on theoretical considerations and empirical analyses. She shows that retailer should focus on the interdependencies between major purchase channels and emphasizes the need to identify supportive stimuli and cues, such as integration services and online- and omni-channel-specific marketing instruments, to support such transfers and improve behavioral outcomes at the retailer and channel level.
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    Blockchain and the Commons
    (Routledge, 2023) Papadimitropoulos, Vangelis
    Recent years have seen a surge of interest in ‘the commons'based on a simple yet radical idea: great improvements in production and management could be achieved by reducing barriers to knowledge exchange and power-sharing. Ranging from meadows, forests and parks to language, open-source software (FLOSS and Blockchain) and 3D printers, the commons are distributed or common property resources/infrastructures that are self-managed by their user communities. While acknowledging the significant contributions that can be made through commons-based peer production, this book provides a critical examination of the commons with the aim of contributing to their long-term sustainability. In particular, the book examines the relation of Blockchain to the commons by illustrating the case study of the Commons Stack.Drawing on a range of interdisciplinary ideas and methodologies, the book argues that there are a number of economic and social barriers that are obstructing the wider reproduction of the commons.
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    Secure Data Science : Integrating Cyber Security and Data Science
    (CRC Press, 2022) Thuraisingham, Bhavani; Kantarcioglu, Murat; Khan, Latifur
    Secure data science, which integrates cyber security and data science, is becoming one of the critical areas in both cyber security and data science. This is because the novel data science techniques being developed have applications in solving such cyber security problems as intrusion detection, malware analysis, and insider threat detection. However, the data science techniques being applied not only for cyber security but also for every application area—including healthcare, finance, manufacturing, and marketing—could be attacked by malware. Furthermore, due to the power of data science, it is now possible to infer highly private and sensitive information from public data, which could result in the violation of individual privacy.
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    SQL for Data Scientists : A Beginner's Guide for Building Datasets for Analysis
    (Wiley, 2021) Teate, Renee M. P.
    Jump-start your career as a data scientist—learn to develop datasets for exploration, analysis, and machine learning SQL for Data Scientists: A Beginner's Guide for Building Datasets for Analysis is a resource that's dedicated to the Structured Query Language (SQL) and dataset design skills that data scientists use most. Aspiring data scientists will learn how to how to construct datasets for exploration, analysis, and machine learning. You can also discover how to approach query design and develop SQL code to extract data insights while avoiding common pitfalls. You may be one of many people who are entering the field of Data Science from a range of professions and educational backgrounds, such as business analytics, social science, physics, economics, and computer science. Like many of them, you may have conducted analyses using spreadsheets as data sources, but never retrieved and engineered datasets from a relational database using SQL, which is a programming language designed for managing databases and extracting data.
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    Data And Society
    (World Scientific, 2022) Beynon-Davies, Paul
    Most literature thinks of the relationship between data and society as additive, meaning that data and society are seen as two separate sets of things but which overlap to form an intersection. The literature then goes off to unpack the intersection of the two circles and partners the term data in this manner with terms descriptive of the domain of society — ownership, control, surveillance, and privacy, to name but a few.Within this book, we want to promote an alternative viewpoint of the relationship between data and society. Rather than explaining how data fits with or contributes to some burning societal issues, we want to explain how data is constitutive of many such issues. The term constitutive is used here in the sense of data having power to institute, establish, or enact society.
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    Algorithms For Big Data
    (World Scientific, 2020) Feldman, Moran
    This unique volume is an introduction for computer scientists, including a formal study of theoretical algorithms for Big Data applications, which allows them to work on such algorithms in the future. It also serves as a useful reference guide for the general computer science population, providing a comprehensive overview of the fascinating world of such algorithms.To achieve these goals, the algorithmic results presented have been carefully chosen so that they demonstrate the important techniques and tools used in Big Data algorithms, and yet do not require tedious calculations or a very deep mathematical background.