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Data Science for Entrepreneurship: Principles and Methods for Data Engineering, Analytics, Entrepreneurship, and the Society: Classroom Companion: Business

Editat de Werner Liebregts Willem-Jan Van den Heuvel Editat de Willem-Jan van den Heuvel Damian A. Tamburri Editat de Arjan van den Born Florian Böing-Messing, Anne J. F. Lafarre
en Limba Engleză Hardback – 25 mar 2023
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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Specificații

ISBN-13: 9783031195532
ISBN-10: 3031195531
Pagini: 532
Ilustrații: XIV, 532 p. 82 illus., 45 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 1.07 kg
Ediția:2023
Editura: Springer International Publishing
Colecția Springer
Seria Classroom Companion: Business

Locul publicării:Cham, Switzerland

Cuprins

The Unlikely Wedlock Between Data Science and Entrepreneurship.- Data Engineering: Big Data Engineering.- Data Governance.- Big Data Architectures.- Data Engineering in Action.- Data Analytics: Supervised Machine Learning in a Nutshell.- An Intuitive Introduction to Deep Learning.- Sequential Experimentation and Learning.- Advanced Analytics on Complex Industrial Data.- Data Analytics in Action.- Data Entrepreneurship.- Data-Driven Decision Making.- Digital Entrepreneurship.- Strategy in the Era of Digital Disruption.- Digital Servitization in Agriculture.- Entrepreneurial Finance.- Entrepreneurial Marketing.- Data and Society: Data Protection Law and Responsible Data Science.- Perspectives from Intellectual Property Law.- Liability and Contract Issues Regarding Data.- Data Ethics and Data Science.- Value Sensitive Software Design.- Data Science for Entrepreneurship: The Road Ahead. 


Notă biografică

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).


Textul de pe ultima copertă

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.


Caracteristici

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