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The Elements of Big Data Value

Inside this Book

If you make use of this material, you may credit the authors as follows:

Curry Edward et al. (Editors), "The Elements of Big Data Value", Springer Nature, 2021, DOI: 10.1007/978-3-030-68176-0, License:

This open access book presents the foundations of the Big Data research and innovation ecosystem and the associated enablers that facilitate delivering value from data for business and society. It provides insights into the key elements for research and innovation, technical architectures, business models, skills, and best practices to support the creation of data-driven solutions and organizations. The book is a compilation of selected high-quality chapters covering best practices, technologies, experiences, and practical recommendations on research and innovation for big data. The contributions are grouped into four parts: · Part I: Ecosystem Elements of Big Data Value focuses on establishing the big data value ecosystem using a holistic approach to make it attractive and valuable to all stakeholders. · Part II: Research and Innovation Elements of Big Data Value details the key technical and capability challenges to be addressed for delivering big data value. · Part III: Business, Policy, and Societal Elements of Big Data Value investigates the need to make more efficient use of big data and understanding that data is an asset that has significant potential for the economy and society. · Part IV: Emerging Elements of Big Data Value explores the critical elements to maximizing the future potential of big data value. Overall, readers are provided with insights which can support them in creating data-driven solutions, organizations, and productive data ecosystems. The material represents the results of a collective effort undertaken by the European data community as part of the Big Data Value Public-Private Partnership (PPP) between the European Commission and the Big Data Value Association (BDVA) to boost data-driven digital transformation.


Information Storage And Retrieval, Business And Management, General, Innovation/technology Management, The Computer Industry, Big Data, Innovation And Technology Management, Technology Commercialization, Digital Transformation, Innovation Spaces, Data-driven Innovation, Data Analytics, Technology Management, Data Ecosystems, Data Protection, Big Data Business Models, Open Access, Information Retrieval, Data Warehousing, Business & Management, Research & Development Management, Industrial Applications Of Scientific Research & Technological Innovation, Information Technology Industries, Databases

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