Universität Wien
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040190 KU Advanced Topics in Business Informatics (MA) (2023S)

Business Intelligence und Advanced Analytics

4.00 ECTS (2.00 SWS), SPL 4 - Wirtschaftswissenschaften
Continuous assessment of course work
MIXED

As the practical exercises will take place in the PC seminar room, only 25 registrations will be admitted to the course combination, as otherwise there will be no practice places for everyone.

In order to be admitted to the course, you must be punctual for the preliminary discussion/1st course unit. Unexcused absence will result in the loss of the course place.
Moodle

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 25 participants
Language: German

Lecturers

Classes (iCal) - next class is marked with N

The following dates from the overview concern the tutorial accompanying the course:
(Attendance is strongly recommended, no compulsory attendance)
ATTENTION: SLIGHT CHANGES STILL POSSIBLE!
TUE weekly 14.03.-23.05.2023 16:45-18:15 PC-SR 2 OMP;
TUE 28.03.2023 18:30-20:00 PC-SR 2 OMP;
TUE 02.05.2023 18:30-20:00 PC-SR 2 OMP;

  • Thursday 02.03. 18:30 - 20:00 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
  • Thursday 09.03. 11:30 - 16:30 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
    PC-Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Thursday 09.03. 16:45 - 18:15 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
    PC-Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Thursday 09.03. 18:30 - 20:00 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
    PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
    PC-Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Tuesday 14.03. 16:45 - 18:15 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Thursday 16.03. 18:30 - 20:00 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
  • Tuesday 21.03. 16:45 - 18:15 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Thursday 23.03. 18:30 - 20:00 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
  • Tuesday 28.03. 16:45 - 18:15 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Tuesday 28.03. 18:30 - 20:00 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Thursday 30.03. 18:30 - 20:00 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
  • Tuesday 18.04. 16:45 - 18:15 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Thursday 20.04. 18:30 - 20:00 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
  • Tuesday 25.04. 16:45 - 18:15 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Thursday 27.04. 18:30 - 20:00 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
  • Tuesday 02.05. 16:45 - 18:15 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Tuesday 02.05. 18:30 - 20:00 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Thursday 04.05. 18:30 - 20:00 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
  • Tuesday 09.05. 16:45 - 18:15 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Thursday 11.05. 18:30 - 20:00 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
  • Tuesday 16.05. 16:45 - 18:15 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Tuesday 23.05. 16:45 - 18:15 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Thursday 25.05. 18:30 - 20:00 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Thursday 01.06. 16:45 - 18:15 Hörsaal 15 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 01.06. 18:30 - 20:00 Hörsaal 15 Oskar-Morgenstern-Platz 1 2.Stock

Information

Aims, contents and method of the course

Selected sub-areas from Business Intelligence, Data Warehouse, Data Mining, OLAP as well as topics around Big Data and Predictive Analytics

Assessment and permitted materials

Collaboration, solution of tasks, written exams (without documents), case studies

Minimum requirements and assessment criteria

• Theory

o Written exam (50%) (without documents)

• Practical/Project (incl. programming part) (min. 40% from both parts)

o Development of a case study (35%)

o Implementation of practical tasks (15%)

All partial performances of the project part have to be submitted via Moodle in due time!

• Compulsory attendance

In total, more than 50% of the requirements must be fulfilled in order to pass this course.

Assessment:
– Grading (rating scale):

Grad

100,00 % 88,00 % 1

87,99 % 75,00 % 2

74,99 % 63,00 % 3

62,99 % 50,00 % 4

49,99 % 0,00 % 5

Examination topics

Content covered in the course units + additional materials on the eLearning platform Moodle

Reading list

The literature list will be published on Moodle.

Association in the course directory

Last modified: Th 09.03.2023 12:28