The fast-paced technological development and the plethora of data create numerous opportunities waiting to be exploited by entrepreneurs. 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.
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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).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.
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