inf604 - Business Intelligence I (Course overview)

inf604 - Business Intelligence I (Course overview)

Department of Computing Science 6 KP
Module components Semester courses Wintersemester 2019/2020 Examination
  • No access 2.01.604 - Business Intelligence Show lecturers
    • Viktor Dmitriyev
    • Dr.-Ing. Andreas Solsbach

    Tuesday: 14:00 - 16:00, weekly (from 15/10/19), VL, Location: A04 2-221
    Friday: 08:00 - 10:00, weekly (from 18/10/19), Ü, Location: (A04 3-321)
    Dates on Friday, 14.02.2020 10:00 - 12:00, Monday, 15.06.2020 13:00 - 13:30, Thursday, 02.07.2020, Tuesday, 04.08.2020 09:00 - 11:00, Location: A04 2-221, A14 0-030, A14 0-031 (+1 more)

Hinweise zum Modul

No participant requirement


At the end of the lecture period

Module examination

Written exam max. 120 minutes

Skills to be acquired in this module

Objective of the module/skills:
Current module provides basics of business intelligence with focus on enterprises and strong emphasis on data warehousing technologies. Students of the course are provided with knowledge, which reflects current research and development in a data analytic domain.
Professional competence
The students:

  • name and recognize the role of business intelligence as past of daily business process
  • being able to analyse advantages and disadvantages of different approaches and methods of the data analytics and being able to apply them in simple case studies
  • obtain theoretical knowledge about data collection and modelling processes, including most applicable approaches and best practices

Methodological competence
The students:

  • being able to execute typical tasks of business intelligence, and also being able to deepen knowledge on different approaches and methods
  • gain a hans on experience and being able to understand advantages and disadvantages of different methods and being able to use obtained knowledge in most efficient ways

Social competence
The students:

  • build solutions based on case studies given to the group, for example solving the issue of a factless fact table
  • discuss solutions on a technical level
  • present obtained case studies solutions as part of the exercises

The students:

  • critically review provided data and information