Editors:
- Explores various aspects of data engineering and information processing
- Covers essential topics in data-centric business, such as information generation, representation, structuring, organization, storage, retrieval, navigation, human factors in information systems, and the use of information
- Discusses key processes and procedures used in information/data processing and management
Part of the book series: Lecture Notes on Data Engineering and Communications Technologies (LNDECT, volume 42)
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Table of contents (10 chapters)
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Front Matter
About this book
Building on the authors’ previous work, this book addresses key processes and procedures used in information/data processing and management. Modern methods of business information processing, which draw on artificial intelligence, big data, and cloud-based storage and processing, are opening exciting new opportunities for doing business on the basis of information technologies. Thus, in this third book, the authors continue to explore various aspects – technological as well as business and social – of the information industries. Further, they analyze the challenges and opportunities entailed by these kinds of business.
Editors and Affiliations
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Department of Infocommunication Engineering, Faculty of Infocommunication, Kharkiv National University of Radio Electronics, Kharkiv, Ukraine
Dmytro Ageyev, Tamara Radivilova
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Department of e-Business, Faculty of Business, Economics and Statistics, University of Vienna, Vienna, Austria
Natalia Kryvinska
Bibliographic Information
Book Title: Data-Centric Business and Applications
Book Subtitle: Evolvements in Business Information Processing and Management (Volume 3)
Editors: Dmytro Ageyev, Tamara Radivilova, Natalia Kryvinska
Series Title: Lecture Notes on Data Engineering and Communications Technologies
DOI: https://doi.org/10.1007/978-3-030-35649-1
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Softcover ISBN: 978-3-030-35648-4Published: 28 January 2020
eBook ISBN: 978-3-030-35649-1Published: 03 January 2020
Series ISSN: 2367-4512
Series E-ISSN: 2367-4520
Edition Number: 1
Number of Pages: X, 228
Number of Illustrations: 48 b/w illustrations, 22 illustrations in colour
Topics: Data Engineering, Computational Intelligence, Big Data/Analytics, Artificial Intelligence