Data Science for Entrepreneurship
Principles and Methods for Data Engineering, Analytics, Entrepreneurship, and the Society
Series: Classroom Companion: Business;
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Product details:
- Edition number 2023
- Publisher Springer International Publishing
- Date of Publication 26 March 2024
- Number of Volumes 1 pieces, Book
- ISBN 9783031195563
- Binding Paperback
- See also 9783031195532
- No. of pages532 pages
- Size 235x155 mm
- Language English
- Illustrations XIV, 532 p. 82 illus., 45 illus. in color. Illustrations, black & white 548
Categories
Long description:
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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Table of Contents:
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.
