Overview
- Offers a practical approach to leverage big data and AI for new value creation
- Compiles detailed examples and cases on data science and its applications
- Provides discussion questions at the end of each chapter for classroom use
Part of the book series: Classroom Companion: Business (CCB)
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Table of contents (22 chapters)
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Front Matter
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Data Engineering
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Front Matter
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Keywords
- Applications of data science in entrepreneurship
- Data science for startups
- Cyberphysical systems
- Data engineering methods
- Process mining
- Data science lecture notes
- Data science for business model creation
- Data-driven SCM intelligence
- Servitization and data-driven innovation
- Artificial intelligence and entrepreneurship
About this book
The fast-paced technological development and the plethora of data create numerous opportunities waiting to be exploited by entrepreneurs. This book provides a detailed, yet practical, introduction to the fundamental principles of data science and how entrepreneurs and would-be entrepreneurs can take advantage of it. It walks the reader through sections on data engineering, and data analytics as well as sections on data entrepreneurship and data use in relation to society. The book also offers ways to close the research and practice gaps between data science and entrepreneurship. By having read this book, students of entrepreneurship courses will be better able to commercialize data-driven ideas that may be solutions to real-life problems. Chapters contain detailed examples and cases for a better understanding. Discussion points or questions at the end of each chapter help to deeply reflect on the learning material.
Editors and Affiliations
About the editors
Werner Liebregts is an Assistant Professor of Data Entrepreneurship at the Jheronimus Academy of Data Science (JADS, Tilburg University, the Netherlands), and a secretary of the Dutch Academy of Research in Entrepreneurship (DARE). His research focuses on how entrepreneurs and entrepreneurship scholars can leverage data science and AI for new value and new knowledge creation, respectively.
Willem-Jan van den Heuvel is a Full Professor of Data Engineering at the Jheronimus Academy of Data Science (JADS, Tilburg University, the Netherlands), and the Academic Director of the JADS’ Data Governance lab. His research interests are at the cross-junction of software engineering, data science and AI, and distributed enterprise computing.
Arjan van den Born is a Full Professor of Data Entrepreneurship and the former Academic Director of the Jheronimus Academy of Data Science (JADS), a joint initiative of Tilburg University and the Eindhoven University of Technology, both locatedin the Netherlands. He is also the Managing Director of a Regional Development Agency (RDA) in the Utrecht region (the Netherlands).Bibliographic Information
Book Title: Data Science for Entrepreneurship
Book Subtitle: Principles and Methods for Data Engineering, Analytics, Entrepreneurship, and the Society
Editors: Werner Liebregts, Willem-Jan van den Heuvel, Arjan van den Born
Series Title: Classroom Companion: Business
DOI: https://doi.org/10.1007/978-3-031-19554-9
Publisher: Springer Cham
eBook Packages: Business and Management, Business and Management (R0)
Copyright Information: Springer Nature Switzerland AG 2023
Hardcover ISBN: 978-3-031-19553-2Published: 25 March 2023
Softcover ISBN: 978-3-031-19556-3Published: 26 March 2024
eBook ISBN: 978-3-031-19554-9Published: 23 March 2023
Series ISSN: 2662-2866
Series E-ISSN: 2662-2874
Edition Number: 1
Number of Pages: XIV, 532
Number of Illustrations: 37 b/w illustrations, 45 illustrations in colour
Topics: Entrepreneurship, Big Data/Analytics, Data Engineering, Big Data, Innovation/Technology Management