Business Intelligence & Data Science

Type and Deduction (in German only):

2. Spezialisierung im Bereich Wirtschaftsinformatik im Master Wirtschaftsinformatik: Modul BWL-MA-WI-BIDS
3. Wahlpflichtbereich im Master Wirtschaftsinformatik: Modul BWL-MA-WI-BIDS
2. Wahlpflichtbereich im Master IT-Management und -Consulting: Modul WiWi-MA-WI-BIDS
Im Schwerpunktfach Operations and Supply Chain Management per Queranrechnung
Im Methodenbereich des Master Betriebswirtschaft (Zulassung ab WiSe15/16)
Im Schwerpunktfach Business Analytics des Master Betriebswirtschaft per Queranrechnung
Im Bereich Allgemeine Betriebswirtschaftslehre und Methoden des Master Betriebswirtschaft (Zulassung bis WiSe15/16)
Modul aus Allgemeine BWL und Methoden im Master Lehramt an beruflichen Schulen

Requirements

None. Knowledge in the areas information management, multivariate statistics and programming can be of help, but are not required.

Scope of Deduction

6 CP
3 SWS (2 SWS lecture, 1 SWS tutorial)

Lecturers

Dr. Robert Stahlbock

Course Dates

Mon, 2:00 - 5:00 pm, ESA A

Registration

In order to participate in this course, it is obligatory to register in STiNE during the STiNE registration periods.

Course Evaluation

Evaluation Type: exam

As soon as they are known, the exact examination dates will be announced in STiNE.

Registration for the exams in STiNE well within the registration periods is mandatory (also for students who repeat the exam!).

Each business process engenders a certain amount of data. If, for instance, a book is ordered via Amazon, this transaction provides data about the customer, the ordered book, (if applicable) which other books have been looked at before the actual order, the time in which the order has been processed, the chosen payment method, etc. Due to the consequent informatin systems support of business processes (esp. ERP systems) all of these data are saved and so are basically available for an evaluation. Consequently, the interest in techniques and methods for evaluating data has increased rapidly within the last years. In this context, the buzzword Business Intelligence indicates an integrated IT-masterplan, which is able to offer feasible and interlinked solutions for different decision-making systems (Gluckowski/Kemper, 2006).
Main topic of this lecture are systems and methods for supporting business planning and decision problems.Therefore, especially issues relating to customer relationship management are considered. Within the framework of the latter, business intelligence and data mining applications are used particularly frequently.

Data mining is generally regarded as an approach to uncovering novel, potentially business-relevant, intelligible patterns or connections in (large) databases and can be divided into the subregions of the predictive (directed / supervised) and descriptive (non-directional / unsupervised) data mining (see Fayyad et al, 1996;. Berry / Linoff, 2004). During the lecture the operational applications of such techniques and their methodological foundations are discussed in detail. Moreover, the steps taken before and after the actual analysis , for example, the data preparation of the result analysis are being discussed.
Another Session is dedicated to applications of data mining techniques in the WWW-environment. For example, the term Web Mining has been established as a superset of techniques for the analysis of usage patterns (Lane Usage Mining), linking structures (web structure mining) and Web sites (Web Content Mining) . The latter becomes especially more important in terms of evaluating news articles or blog posts and is, inter alia, used for prediction in marketing and financial market developments. General principles of Web-mining and special aspects of the analysis of textual content in Opinion Mining are accordingly also a subject of the lecture.

Course Material

The material is provided via STiNE for students who are registered for the course.

Literature

Literature recommendations are given during lectures.