Business Analytics for Decision Making

Participants commence their journey with an exploration of cluster analysis, a vital technique for data reduction essential for market segmentation. This module provides a comprehensive understanding of hierarchical and k-Means clustering, utilizing tools such as Excel and XLMiner to enhance proficiency in cluster analysis.

This module delves into the realm of Monte Carlo simulation, equipping learners with the skills to add uncertainty to spreadsheet models, analyze results, and leverage historical data for modeling uncertainty. The acquired knowledge is applied through assignments and discussions, offering practical insights into the application of Monte Carlo simulation.

With a focus on optimization and decision making, this module empowers participants to formulate and solve optimization problems, evaluate scenarios, and visualize results to gain practical insights. Learners explore real-world applications of optimization, gaining valuable expertise in identifying the best options among multiple alternatives.

This advanced module delves into models for better decisions, covering binary optimization problems, metaheuristic optimization, chance constraints, value at risk, and simulation optimization. Participants gain a deeper understanding of how organizations optimize their systems to make better decisions, enhancing their decision-making capabilities.