288 pages | 57 B/W Illus.
Together, Big Data, high-performance computing, and complex environments create unprecedented opportunities for organizations to generate game-changing insights that are based on hard data. Business Analytics: An Introduction explains how to use business analytics to sort through an ever-increasing amount of data and improve the decision-making capabilities of an organization.
Covering the key areas of business analytics, the book explores the concepts, techniques, applications, and emerging trends that professionals across a wide range of industries need to be aware of. Better detection of fraud through visual analytics or better prediction of the likelihood of someone getting an infection while in the hospital are just a few examples of where analytics can play a positive role.
As the field of business analytics continues to emerge rapidly, there is a need for a reliable textbook and reference on the subject. Filling this need, this book is suitable for graduate-level students and undergraduate seniors. It maintains a focus on only the key areas so the material can be covered adequately in a one-semester or one-quarter course. Each chapter includes software-generic exercises, labs, and associated answers to the exercises/labs.
Author Jay Liebowitz recently had an article published in The World Financial Review.
The Value of Business Analytics; Evan Stubbs
Producing Insights from Information through Analytics; Frank Stein and Arnold Greenland
Executive/Performance Dashboards; Patrick Yurgosky
Data Mining: Helping to Make Sense of Big Data; Barry Keating
Big Data Analytics for Business Intelligence; Onur Savas, Tung Thanh Nguyen, and Julia Deng
Text Mining Fundamentals; Luca Toldo
Neural Network Fundamentals; Angelos Barmpoutis
Measuring Success in Social Media: An Information Strategy in a Data Obese World; Jeremy P. Floyd
The Legal and Privacy Implications of Data Mining; Elana Zeide
Epilogue: Parting Thoughts about Business Analytics; Jay Liebowitz