Business Analytics: Technologien, Methoden und Konzepte [BA]

Business analytics as a discipline makes use of a variety of methodological and technological approaches for the analytical evaluation of company-relevant data from different source systems in order to gain insights into past, present and future business activities. Of interest are, for example, aggregated or filtered insights about the company’s performance or the uncovering of previously unknown correlations, trends and patterns in order to generate new knowledge and improve the company’s decisions. For this purpose, the approach makes use of different methods of diverse origin, such as from the fields of statistics, data mining and artificial intelligence.

The practice-oriented course introduces the basics of the topic and provides an overview of relevant concepts, methods and technologies. Here, the focus is particularly on the subarea of predictive analytics and the approaches of (supervised) machine learning for the creation of predictive models. Using a typical pipeline for data business analytics projects, the basic steps and principles of predictive modeling are illustrated and supported with example approaches (e.g., model training using deep neural networks). The course consists of a lecture to convey conceptual content and an accompanying computer-based exercise in which selected aspects are deepened and implemented using the Python programming language.

This course is taught together with Prof. Zschech (Intelligent Information Systems). For details about the course, see StudOn.