The course is an introduction to business analytics. It explores how businesses can create value with data. 

In Prof. Peukert’s part of the course, the focus will be on two main topics:

(1) How to formalize, structure, and optimize decision problems and

(2) how to structure and analyze large data sets.

Participants will develop an understanding of cases where causality is important and the cases where we can make predictions based on correlations. We will use simple experimental methods for the former, and simple predictive analytics methods for the latter.

In Prof. Pieper’s part, participants learn to think in terms of data use cases and explore six basic areas for data-driven business insights (i.e., 1. better decisions; 2. better understanding customers; 3. better services; 4. better products; 5. better processes; 6. monetizing data). More specifically, participants learn to break down the process of creating value with data into a structured sequence of actionable steps. These steps can be applied across all industries and all kinds of businesses, ranging from small "quick wins" to majorly transformational initiatives.  

Participants will be evaluated based on individual homework assignments. The final grade is calculated as the average grade of all assignments with equal weighting.