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

ISBN-13: 9783031195532 / Angielski / Twarda / 2023 / 840 str.

Werner Liebregts; Willem-Jan Van Den Heuvel; Damian A. Tamburri
Data Science for Entrepreneurship: Principles and Methods for Data Engineering, Analytics, Entrepreneurship, and the Society Werner Liebregts Willem-Jan Va Damian A. Tamburri 9783031195532 Springer - książkaWidoczna okładka, to zdjęcie poglądowe, a rzeczywista szata graficzna może różnić się od prezentowanej.

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

ISBN-13: 9783031195532 / Angielski / Twarda / 2023 / 840 str.

Werner Liebregts; Willem-Jan Van Den Heuvel; Damian A. Tamburri
cena 342,95
(netto: 326,62 VAT:  5%)

Najniższa cena z 30 dni: 308,41
Termin realizacji zamówienia:
ok. 22 dni roboczych.

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inne wydania

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.

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.

Kategorie:
Nauka, Ekonomia i biznes
Kategorie BISAC:
Business & Economics > Przedsiębiorczość
Business & Economics > Industries - Computers & Information Technology
Computers > Data Science - General
Wydawca:
Springer
Seria wydawnicza:
Classroom Companion: Business
Język:
Angielski
ISBN-13:
9783031195532
Rok wydania:
2023
Dostępne języki:
Numer serii:
000962575
Ilość stron:
840
Oprawa:
Twarda

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. 


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 located in 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.


Van Den Heuvel, Willem-Jan Willem-Jan van den Heuvel is Associate Professor i... więcej >


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