TY - BOOK ID - 118414288 TI - Data science for entrepreneurship : principles and methods for data engineering, analytics, entrepreneurship, and the society AU - Heuvel, Willem-Jan van den AU - Van den Born, Arjan PY - 2023 SN - 303119554X 3031195531 PB - Cham, Switzerland : Springer, DB - UniCat KW - Entrepreneurship. KW - New business enterprises. KW - Business information services. KW - Engineering—Data processing. KW - Big data. KW - Business. KW - Management science. KW - IT in Business. KW - Data Engineering. KW - Big Data. KW - Business and Management. KW - Data sets, Large KW - Large data sets KW - Data sets KW - Business KW - Business enterprises KW - Information services KW - Business starts KW - Development stage enterprises KW - How to start a business KW - New companies KW - Start-up business enterprises KW - Start-up companies KW - Start-ups (Business enterprises) KW - Starting a business KW - Startups (Business enterprises) KW - Business incubators KW - Quantitative business analysis KW - Management KW - Problem solving KW - Operations research KW - Statistical decision KW - Trade KW - Economics KW - Commerce KW - Industrial management KW - Entrepreneur KW - Intrapreneur KW - Capitalism UR - https://www.unicat.be/uniCat?func=search&query=sysid:118414288 AB - 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. ER -