Data Analysis and Business Intelligence
Integrated course, 5.00 ECTS
Course content
Advanced biostatistics with R (explorative data analysis, risk assessment, association measures, hypothesis testing), dispositive data (DWH, ODS) OLAP, ETL, multi-dimensional data modeling, data mining, DWH architectures, multi-dimensional modeling, reports according to IBCS
Learning outcomes
The students understand decision-making processes in the health care sector in particular at the management level. They can analyze complex facts and prepare decisions based on facts and data.
Recommended or required reading and other learning resources / tools
Books: Kemper et al.: Business Intelligence; Weiß: Basiswissen medizinische Statistik; Fahrmeir et al.: Statistik - Der Weg zur Datenanalyse; Bruce et al.: Practical Statistics for Data Scientists 50+ Essential Concepts Using R and Python
Mode of delivery
Lecture, group work, lab practical, presentation
Prerequisites and co-requisites
None
Assessment methods and criteria
Lecture: Exam; Tutorial: Continuous Assessment