Business Intelligence & Analytics(E)

Master`s course

Graduates/students: Datawarehousing: * Knows classification and demarcation of data warehousing, OLAP, data mining and reporting in the field of business intelligence * Knows areas of application and potential use of data warehousing, OLAP and data mining * Can assess areas of application and fields of application * Can record reporting requests from business * Can convert Reporting Requirements into Data Models * Can design and implement data warehouse databases * Knows different data formats / interface formats * Knows methods of data conversion * Can convert data * Can load a data warehouse * Knows OLAP - Terms * Can design and implement OLAP cubes * Can design access to OLAP cubes Datamining / Data Science: * Knows Datamining and Data Science algorithms and techniques * Knows the data mining / data science process * Can process the data for data mining * Can apply data mining methods to problems * Can present the results from data mining * Can create simple rules * Can implement/customize selected algorithms * Knows BI - Functionalities of ERP Systems * Knows products and manufacturers of BI solutions (backend, frontend) (Microsoft, Oracle, SAP, Infor, Crystal Report, etc.) Process Mining: * Knows goals of Process Mining * Knows prerequisites for process mining * Knows benefits, limitations, application areas of Process Mining * Has an overview of Process Mining Software

not applicable

* Concept of business intelligence and specific aspects such as datawarehouse, OLAP. * Methods and techniques of data mining and process mining * Techniques and up-to-date tools in the field of data warehousing & data mining * Case studies or projects in the subject area with practical application of tools * Tools in the field of business intelligence

Runkler Th.; Information Mining; vieweg; 2000 Langit L.; Smart Business Intelligence Solutions with Microsoft SQL Server; Microsoft Press; 2008 Petersohn H.; Data Mining; Oldenbourg; 2005 Provost F., Fawcett T.; Data Science for Business; O’Reilly; 2013 Milton M.; Head First Data Analysis; O’Reilly; 2009 van der Aalst W. M.P.; Process Mining – Data Science in Action; Heidelberg; 2016;. 2nd edition

Written exam

English

6

15

4.0

Lecture, individual work with software, group work, presentation and discussion of tasks

3

Dr. Arnim Franzmann

2

DAT.2

integrated lecture

Compulsory

not applicable