ERP Systems & Business Process Management PT
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Datawarehousing & Business Intelligence (E, T)

level of course unit

second cycle, Master

Learning outcomes of course unit

Graduates/students:
- know field of application and use potential of data mining
- know technologies and procedures of data mining
- can gather reporting requirements from business (technical specifications)
- can apply data mining methods to problems
- can illustrate the results from data mining
- know BI functionalities of ERP systems
- know kind and procedure of data migration
- know methods of data conversion

prerequisites and co-requisites

not applicable

course contents

Data warehousing concept and related concepts such as OLAP, as well as methods and techniques for data mining. Techniques and current tools from the field of data warehousing & data mining. Case studies or projects with concrete, practical application. Tools for connecting business intelligence systems.

recommended or required reading

Bauer, Andreas; Günzel, Holger: Data Warehouse Systeme: Architektur, Entwicklung, Anwendung.- Heidelberg: dpunkt.verlag, 2004 Date, Chris J.; Darwen, Hugh: SQL - Der Standard.- Addison-Wesley, 1998 Meier, Andreas; Wüst, Thomas: Objektorientierte und objektrelationale Datenbanken.- dpunkt, 2003 Otte, Ralf; Otte, Viktor; Kaiser, Volker: Data Mining für die industrielle Praxis.- Hanser, 2004 Ramiz, Elmasri; Shamkant, B. Navathe: Grundlagen von Datenbanksystemen.- Pearson, 2002

assessment methods and criteria

Standardized exam (Multiple choice and short answers)

language of instruction

English

number of ECTS credits allocated

2

planned learning activities and teaching methods

Lecture, group work, presentation and task discussion

semester/trimester when the course unit is delivered

3

name of lecturer(s)

Dr. Franzmann Arnim

year of study

2.year of studies

recommended optional program components

not applicable

course unit code

V.DAT.3

type of course unit

compulsory (lecture)

mode of delivery

In-class course

work placement(s)

not applicable