Name: Data Science for Entrepreneurship: Principles and Methods for Data Engineering, Analytics, Entrepreneurship, and the Society (en Inglés)
SKU: 57047542
Price: 87.87 USD
Availability: InStock
Author: Liebregts, Werner ; Van Den Heuvel, Willem-Jan ; Van Den Heuvel, Willem-Jan

portada Data Science for Entrepreneurship: Principles and Methods for Data Engineering, Analytics, Entrepreneurship, and the Society (en Inglés)

Data Science for Entrepreneurship: Principles and Methods for Data Engineering, Analytics, Entrepreneurship, and the Society (en Inglés)

Formato

Libro Físico

Editorial

Springer

Autor

Liebregts, Werner ; Van Den Heuvel, Willem-Jan ; Van Den Heuvel, Willem-Jan

Idioma

Inglés

N° páginas

532

Encuadernación

Tapa Dura

Dimensiones

23.8x16x3 cm

Peso

1.07 kg.

ISBN13

9783031195532

N° edición

2023rd

Categorías

Ciencia y análisis de datos: generalidades
Emprendimiento y emprendedores
Industrias de la tecnología de la información
Análisis y captura de datos

Data Science for Entrepreneurship: Principles and Methods for Data Engineering, Analytics, Entrepreneurship, and the Society (en Inglés)

Liebregts, Werner ; Van Den Heuvel, Willem-Jan ; Van Den Heuvel, Willem-Jan (Autor) · Springer · Tapa Dura

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Reseña del libro "Data Science for Entrepreneurship: Principles and Methods for Data Engineering, Analytics, Entrepreneurship, and the Society (en Inglés)"

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.