Big Data Management
Springer International Publishing (Verlag)
978-3-319-45497-9 (ISBN)
Dr. Fausto Pedro García Márquez completed his European Doctorate in Engineering at the University of Castilla-La Mancha (UCLM) in 2004. He received his Engineering degree from the University of Murcia, Spain in 1998, and his Technical Engineering degree at UCLM in 1995 and degree in Business Administration and Management at UCLM in 2006. He has also served as Technician in Labor Risk Prevention by UCLM (2000) and Transport Specialist at the Polytechnic University of Madrid, Spain (2001). He was a Senior Manager at Accenture in 2013/2014, and is currently a Senior Lecturer (Full Professor accredited) at UCLM, an Honorary Senior Research Fellow at the University of Birmingham, UK, a Lecturer at the Instituto Europeo de Postgrado and Director of the Ingenium Research Group. He has been the principal investigator in 3 European Projects and 60 national and corporate research projects. He holds international and national patents, and has authored more than 110 international papers and 10 books. His work has been recognized with 3 International Awards in Engineering Management and Management Science. Dr. Benjamin Lev is a Professor and Head of Decision Sciences at LeBow College of Business. He holds a PhD in Operations Research from Case Western Reserve University. Prior to joining Drexel University, Dr. Lev held academic and administrative positions at Temple University, the University of Michigan-Dearborn and Worcester Polytechnic Institute. He is the Editor-in-Chief of OMEGA – The International journal of Management Science, the Co-Editor-in-Chief of the International Journal of Management Science and Engineering Management, and serves on several other journal editorial boards. He has published over ten books and numerous articles, and has organized many national and international conferences.
Introduction.- The Big Data Business Opportunity.- The Business Transformation by Big Data.- Data Integration and Management Science.- Novel Approaches for Big Data Analytics.- Case Studies: Engineering; Financial; Economic; Business; Project Management.- Signal Processing.
"This book is definitely timely with its ambitious goals to fulfill a big gap in the literature. ... this book provides a valuable collection of perspectives that demonstrate the complexity and diversity of big data, and open avenues for future research. ... This book will be particularly welcome by researchers who are interested in an interdisciplinary approach to big data and have a basic understanding of computer science." (Mingming Cheng, Information Technology & Tourism, Vol. 17, 2017)
“This book is definitely timely with its ambitious goals to fulfill a big gap in the literature. … this book provides a valuable collection of perspectives that demonstrate the complexity and diversity of big data, and open avenues for future research. … This book will be particularly welcome by researchers who are interested in an interdisciplinary approach to big data and have a basic understanding of computer science.” (Mingming Cheng, Information Technology & Tourism, Vol. 17, 2017)
| Erscheinungsdatum | 14.12.2016 |
|---|---|
| Zusatzinfo | XVI, 267 p. 107 illus., 38 illus. in color. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Mathematik / Informatik ► Informatik |
| Mathematik / Informatik ► Mathematik ► Finanz- / Wirtschaftsmathematik | |
| Wirtschaft ► Betriebswirtschaft / Management | |
| Schlagworte | Big Data • Business Analytics • business and management • Business Engineering • Business Information Systems • Business mathematics and systems • Engineering Economics • Engineering Economics, Organization, Logistics, Ma • Engineering: general • Industrial applications of scientific research and • Innovation/Technology Management • It Management • Management Decision Making • management of specific areas • Operating Systems • Operational Research • Operation Research/Decision Theory • Operations Research • Research and Development Management |
| ISBN-10 | 3-319-45497-8 / 3319454978 |
| ISBN-13 | 978-3-319-45497-9 / 9783319454979 |
| Zustand | Neuware |
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