Lehre am Lehrstuhl Business Analytics

Voraussichtlich:

Business Intelligence
Bachelor, English

This course covers foundational process models for data mining, such as CRISP-DM, alongside key machine learning algorithms and data mining models. Students gain hands-on experience with data mining software and learn to select suitable methods for exploratory data analysis, descriptive and predictive modeling—including cluster analysis, association analysis, and classification. The course culminates in an applied analytics project

• Wintersemester 2022/23
• Wintersemester 2023/24
• Wintersemester 2024/25

This course introduces core concepts and methods of Business Intelligence (BI), focusing on data-driven decision-making through automated data processing, analysis, and visualization. Students learn how to extract and interpret information from large datasets and present insights using reports and interactive dashboards. Topics include BI foundations, data preparation and multidimensional modeling (OLAP), KPI development, and decision support. The course also provides hands-on experience with modern BI tools such as Excel, SQL, Power BI, Tableau, Qlik Sense, Looker, and Metabase.

• Sommersemester 2025

This seminar explores data-driven solutions in the fields of data science and decision support. Students address current challenges in areas such as sustainability or healthcare, leading their own projects from planning to the implementation of analytical results. The course focuses on developing essential skills and making a meaningful impact within a single semester.

• Wintersemester 2023/24 (with Prof. Dr. Maxand)
• Wintersemester 2024/25

This seminar explores advanced strategies from Operations Research and Business Analytics to optimize grocery delivery. By examining Revenue Management and Vehicle Routing, students will learn how to make home delivery services both profitable and efficient. The course features discussions on the latest trends and decision-making at various levels, equipping students with practical skills to innovate in the delivery market.

• Sommersemester 2022
• Sommersemester 2023
• Sommersemester 2024

# Evaluation vergangenes Semester #

# Evaluation vergangenes Semester #