Our course equips students with the required skills in statistics, technology, and communication to use data for decision-making. Our partnerships with the private and public sector connect students directly with employment opportunities that match their interests and skill set.
Alexander Sommer, Manager Advanced Analytics, provided us with an overview of the statistical methodologies used for his consulting services. His talk focused on two case studies. First, he and his team applied outlier detection methods, cluster analysis, and simulation methods to improve the quality assurance for a major manufacturer in the automobile sector. Second, he reported on his experience working with the public sector regarding the development of an online recommendation engine. Throughout his presentation, Alexander emphasized the need for data visualization and a structured workflow to facilitate communication with clients. The slides of his lecture are available here.
Nils Wittmann, Analytics Expert, explained how his company uses the latest analytical tools to improve the internal processes of his clients and their interaction with customers. In addition, Nils shared his experiences from two recent projects. First, he reported on the use of regression models and machine learning techniques to tackle customer churn. Second, he presented an ensemble approach to forecast customer demand. Both projects illustrated the need for visualization and communication skills, in addition to technical knowledge, to bridge the gap between data insights and business value.
Susanne Scholten and Martin Slowik, discussed the practice of data analytics in the banking sector with us. As an example, they focused their presentation on default prediction and discussed the bank’s internal model to predict the likelihood of default and the associated losses. They also introduced us to the agile software development environment used at the Deutsche Bank. In that context, Martin stressed the importance of project monitoring and the availability of continuous model validation.
Sebastian Garmann, Peter Koß, and Gregor Teischler, data scientists from the Bundesrechnungshof, explained how data analytics support their auditing of public institutions. For example, they presented a project assessing the effectiveness of communication with the public. In doing so, they combined quantitative analysis and qualitative analysis using approaches such as text mining, word clouds, network graphs, and sentiment scores. Throughout, they emphasized the efforts of the German government to increase access and use of government data by citizens and researchers through numerous open data initiatives.