Online Course Guide of WHU –

Find all modules and courses of our degree programs.

Please use the filters below to select the term (spring or fall) as well as the respective program (BSc, MSc, MBA, Exchange, Doctoral) of your choice for an overview of all modules offered at WHU. The courses are listed under the modules. Please click on a module to see which courses are part of it. If you would like to find out more about a certain course, click on the name of the course to see detail information. The location of the lecture will be reveiled after your course registration on myWHUstudies.

Spring term counts from January - August, fall term counts from September - December.

Important for Exchange Students: As the Full-Time and Part-Time MBA Programs utilize a modular course structure, the dates on which students begin and end the exchange are flexible. Please find here a chronological overview of the preliminary course offering for Spring and Fall.

Spring 2019  ›  Bachelor of Science  ›  Bachelor of Science - 4th Semester  ›  Business Information Systems

Business Information Systems (BIS II)

The course gives an introduction into major aspects of Business Information Systems (BIS) and their role in the enterprise from a managerial point of view. In the first part of the course (BIS I), basic aspects and theories are introduced. In the second part (BIS II), advanced aspects of Information Management are presented and discussed.

Course Code:
MGMT422
Lecturers:
Juniorprof. Dr. Irina Heimbach
Course Type:
BSc Course
Week Hours:
2,0
Term:
Spring 2019
Language:
Englisch
Credits:
3.0
(Please note that exchange students obtain a higher number of credits in the BSc-program at WHU than listed here. For further information please contact directly the International Relations Office.)

1.1 Introduction to the Course

1.2 Foundations and Technologies for Decision Making

1.3 Overview of Business Intelligence, Analytics, and Decision Support

2.1 Conceptual Data Modeling; Entity-Relationship Modeling

2.2 Relational Databases and SQL

3.1 Business Reporting, Visual Analytics and Business Performance Management

3.2 Data Visualization with Tableau

4.1 Predictive Modeling; Data Mining; Decision Trees

4.2 Introduction to Artificial Neural Networks

5.1 Web Analytics, Web Mining and Social Analytics

5.2 Text Analytics, Text Mining, and Sentiment Analysis

6.1.Introduction to Big Data Analytics

6.2 Guest Lecture, tba

6.3 Course Outro and Q & A

Date
Time
Thursday, 07/03/2019
11:30 AM till 03:15 PM
Wednesday, 13/03/2019
11:30 AM till 03:15 PM
Thursday, 21/03/2019
08:00 AM till 11:15 AM
Wednesday, 27/03/2019
11:30 AM till 03:15 PM
Monday, 01/04/2019
03:30 PM till 06:45 PM
Monday, 08/04/2019
11:30 AM till 03:15 PM
  • Improved data literacy and data-analytic thinking
  • Understanding of main concepts related to Decision Support Systems
  • Understanding of basic data mining concepts and approaches
  • Improved skills in working with specific software
R. Sharda et al. (2014): Business Intelligence and Analytics: Systems for Decision Support, 10th Edition, Prentice Hall.

Valacich and George (2017): Modern Systems Analysis and Design, 8thEdition, Pearson.

Lecture

In-class discussions

Online quizzes

Integrated exercises

Practice with software

50% exam,
50% assignments
90