Business Intelligence (BI) is an integrated, company-specific, systematic approach to automating and improving high-volume operational and managerial decisions. BI promotes a shift to fact-based decision making which is important for a company in order to increase productivity and to survive competition. Today it becomes one of the most important management instruments.
Once focus of the module is the state-of-the-art in data warehousing technologies. In particularly, the students willunderstand the role of data in BI and learn how data is processed for gaining information from data. Furthermore we will extensively deal with data analysis (like OLAP) and especially with data mining problems, process mining and text mining. Data mining goes a step beyound the use of statistical techniques and machine learning techniques, and detects without an exact query formulation previously undiscovered connections within the data.
Process mining is a process management technique, which allows the analysis of business processes based on event logs. The object of text mining is to find important information and relationships in large amounts of text.
|Should be visited:||FT: 3rd
PT: 3rd or 5th
|Academic Module Coordinator||Dr. Hans-Friedrich Witschel|
|Lecturers||Dr. Hans-Friedrich Witschel|
|Overall hours||Contact hours: 60 h
Self-Study: 120 h
This course will include topics like:
|Teaching and Learning Methods||
The module is taught through plenary lectures and plenary/group workshops, including case studies, and presentations. Plenary sessions will be accompanied by assignments to be done as homework or during lecture. The results of the assignment have to be presented in class. Class participation is actively encouraged. In the plenary lectures students may be required to orally present results of guided self study or repetition of previous lecture.