Business Analytics with Management Science Models and Methods
Nonfiction, Science & Nature, Technology, Operations Research, Business & Finance, Economics, Statistics, Management & Leadership, Production & Operations Management
| Author: | Arben Asllani | ISBN: | 9780133760668 |
| Publisher: | Pearson Education | Publication: | November 17, 2014 |
| Imprint: | Pearson FT Press | Language: | English |
| Author: | Arben Asllani |
| ISBN: | 9780133760668 |
| Publisher: | Pearson Education |
| Publication: | November 17, 2014 |
| Imprint: | Pearson FT Press |
| Language: | English |
Master decision modeling and analytics through realistic examples, intuitive explanations, and tested Excel templates. Business Analytics with Management Science has been designed to help students, practitioners and managers use business analytics to improve decision-making systems. Unlike previous books, it emphasizes the application of practical management science techniques in business analytics.
Drawing on 20+ years of teaching and consulting experience, Dr. Arben Asllani introduces decision analytics through realistic examples and intuitive explanations – not complex formulae and theoretical definitions. Throughout, Asllani helps practitioners focus more on the crucial input-output aspects of decision making – and less upon internal model complexities that can usually be "delegated" to software.
Master decision modeling and analytics through realistic examples, intuitive explanations, and tested Excel templates. Business Analytics with Management Science has been designed to help students, practitioners and managers use business analytics to improve decision-making systems. Unlike previous books, it emphasizes the application of practical management science techniques in business analytics.
Drawing on 20+ years of teaching and consulting experience, Dr. Arben Asllani introduces decision analytics through realistic examples and intuitive explanations – not complex formulae and theoretical definitions. Throughout, Asllani helps practitioners focus more on the crucial input-output aspects of decision making – and less upon internal model complexities that can usually be "delegated" to software.
