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Data Science for Entrepreneurship - Werner Liebregts - Bog

Bag om Data Science for Entrepreneurship

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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  • Sprog:
  • Engelsk
  • ISBN:
  • 9783031195532
  • Indbinding:
  • Hardback
  • Sideantal:
  • 548
  • Udgivet:
  • 25. marts 2023
  • Udgave:
  • 23001
  • Størrelse:
  • 160x33x241 mm.
  • Vægt:
  • 1080 g.
  • Ukendt - mangler pt..
Forlænget returret til d. 31. januar 2025
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Beskrivelse af Data Science for Entrepreneurship

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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