Data Science and Digital Business [electronic resource] /
García Márquez, Fausto Pedro.editor.
Lev, Benjamin.editor.
This book combines the analytic principles of digital business and data science with business practice and big data. The interdisciplinary, contributed volume provides an interface between the main disciplines of engineering and technology and business administration. Written for managers, engineers and researchers who want to understand big data and develop new skills that are necessary in the digital business, it not only discusses the latest research, but also presents case studies demonstrating the successful application of data in the digital business.
Advanced Regression Models in Data Science -- Data Science Method in Analysis of Flood Risk in Mississippi Gulf Coast Area -- An efficient bundle-like algorithm for data-driven multi-objective bi-level signal design for traffic networks with hazardous material transportation -- Deploying a scalable Data Science environment using Docker -- Data Science and Conversational Interfaces: A new revolution in Digital Business -- After 2017: Managers Exit and Banks Arise.
This book combines the analytic principles of digital business and data science with business practice and big data. The interdisciplinary, contributed volume provides an interface between the main disciplines of engineering and technology and business administration. Written for managers, engineers and researchers who want to understand big data and develop new skills that are necessary in the digital business, it not only discusses the latest research, but also presents case studies demonstrating the successful application of data in the digital business.
Operations research.
Decision making.
Big data.
Management information systems.
E-commerce.
Statistics .
Engineering economics.
Engineering economy.
Operations Research/Decision Theory.
Big Data/Analytics.
Business Information Systems.
e-Commerce/e-business.
Statistics for Business, Management, Economics, Finance, Insurance.
Engineering Economics, Organization, Logistics, Marketing.