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Department Business and Economics
Master

Data Mining Professional

Module: WI II: Business Informatics II
Lecturer: Prof. Dr. Richard Lackes / Julian Sengewald
Scope / Credits: 4 SWS / 7,5 Credits
Course type: Lecture and exercise
Language: German
Date and place:  
Beginning: will not be offered in SS 2023!
Exam:  

Content overview

The course offers an in-depth insight into the possible applications of knowledge management methods in companies and is intended to convey the functionality of
data mining methods. Their implementation will also be learned with a programming language commonly used for the analysis of data (e.g. R, Python). Within the course an independent elaboration of a data-oriented consulting project has to be done.

Learning objectives

Selected methods from the method building set of business informatics are presented and learned and applied by means of practical applications. In particular, the following competences are imparted: Imparting knowledge on the functioning of data mining methods, on the basic application possibilities in the context of business planning incl. discussion of their application limits, on project planning of the application in business planning incl. discussion on economic efficiency. Development of a feeling for application potentials of data mining and knowledge management.

Mastering the basics of a statistical programming language. Advanced procedural knowledge of data mining and its oral presentation. Ability to perform an interface function between technology and entrepreneurial action.