Interest in applying analytics, machine learning, and artificial intelligence to sales and marketing has grown dramatically, with no signs of slowing down. This book provides essential guidance to apply advanced analytics and data mining techniques to real world business applications.
* Essay-based format weaves together technical details and case studies to cut through complexity
* Provides a strong background in business situations that companies face, to ensure that data analytics efforts are productively directed and organized
* Appropriate for both business and engineering students who need to understand the data analytics lifecycle
This book should be considered required reading for analysts, managers and executives seeking to drive business performance and gain competitive advantage through data-driven strategy and decision making. Dr. Haimowitz has distilled his considerable experience into a practical how-to guide that is sure to become a fundamental reference text for the modern analytics practitioner or manager, regardless of industry. Zaheer Benjamin, Group Leader in Business Intelligence & Analytics across Life Sciences, Broadcasting, and Major League Sports
This Data Analytics for Business written by Dr. Ira Haimowitz is an experience laden, practical book with real world examples for data analyst, marketing and business executives. The book is well written and provides a good background in design of the big data organization, data analytical applications, and implementation and delivery of the projects in easy-to- read format. The book is a must read for anyone who is interested in data analytics related to sales, marketing and strategy. Thani Jambulingam Ph.D, Professor, Department of Pharmaceutical and Healthcare Marketing, Haub School of Business, Saint Joseph's University, Philadelphia
Ira J. Haimowitz, Ph.D. is a product management consultant currently specializing in developing and delivering strategy and analytics solutions for the life sciences sector, with over 20 years' experience across industries.
Organizational Design Principles 1. Linking Business Challenges to Big Data Solutions 2. Selling the Big Data Analytics Initiative 3. Organizational Structures for Advanced Analytics 4. Lessons Learned Managing Big Data Departments Analytics Business Applications 5. Segmentation: Categorizing Your Customers 6. Targeting: Getting it Right 7. Campaign Measurement with Learning Objectives 8. Strategic Text Mining 9. Predictive Modeling for Business Implementation and Delivery 10. Privacy Considerations for Big Data Analytics 11. Delivering Results with Actionable Insights 12. Scalability and Long Term Success