Business Intelligence


  1. You get to know strategies, methods, and tools of business intelligence.
  2. Business scenarios illustrate the application of concepts and IT systems for business intelligence.
  3. You gain experience in using methods of a data mining for marketing support.
  4. You work on business cases using instruments like decision trees and artificial neural networks.

Course Structure

The course consists of the lecture and exercises.


Companies are dealing with an ever-increasing volume of data from a wide variety of sources and of different type – text, images, video, sound. Business Intelligence deals with exploring and analyzing these data, extracting relevant information, and turning it into knowledge upon which actions can be taken. The course will give an overview of the main BI concepts, drivers, tools, and technologies.

The main focus will be on the analysis and improvement of a company’s relationships with its customers using business intelligence. Special attention is given to digital and online marketing intelligence (e.g., customer profiling and behavioral insights). In an integrated exercise, students work on marketing-oriented business cases using innovative instruments like data mining, and modern techniques like neural networks, decision trees, and social media mining.

Location and Date

Lecture: Thursday, 13:15 – 14:45, Müller Medien-Hörsaal (H6); beginning April 25th, 2019

Exercise: self-study

More details will be given during the first lecture on April 25th. You will also receive the StudOn password. Please do not send an email for registration.

Course registration

Please do not send an email for registration. More information on the first lecture on April 25th, 2019.

To gain access to the course material (video lectures, slides, forum) please register in the StudOn group: https://www.studon.fau.de/crs2143956.html 



Grading and Exam ID

Written exam (5 ECTS)

70414 (written exam)

70415 (written exam)

Lecture Notes and LoDs

Lecture notes and Lecture-On-Demand packages are available on StudOn: https://www.studon.fau.de/crs2143956_join.html