The growing availability of data and recent developments in optimization methods and machine learning have led to a revolution in modern business analytics. In this Ph.D. dissertation, we propose two frameworks based on mixed-integer optimization that advance business analytics in the context of...

1. Introduction -- 2. Basic Statistics and Functions using R -- 3. Regression Fundamentals -- 4. Simple Linear Regression -- 5. Multiple Regression -- 6. Estimation Intervals and Analysis of Variance -- 7. Predictor Variable Transformations -- 8. Model Diagnostics -- 9. Variable Selection.

Fundamental Notions and Applications of Symbiotic Recursive Pulsative Systems / Marta Franova and Yves Kodratoff -- Cognitive Computing: Quo Vadis? / Anastassia Lauterbach -- Digital Transformations Imperatives: Predictive Goal Processes for Business Model Innovation / Cyrus F. Nourani and...

"The practice of data analytics is changing and modernizing. Innovations in computation and machine learning are creating new opportunities for the data analyst: exposing previously unexplored data to scientific analysis, scaling tasks through automation, and allowing deeper and more accurate...

Introduction -- Business roles -- Functional analytics -- Human resource analytics -- Supply chain analytics -- Customer analytics -- Business process analytics -- Financial analytics -- Implementing business analytics -- Use cases and business application