inf661 - Digital Transformation

inf661 - Digital Transformation

Department of Computing Science 6 KP
Module components Semester courses Sommersemester 2019 Examination
Lecture
  • No access 2.01.661 - Digitale Transformation Show lecturers
    • Christian Janßen, M. Sc.
    • Prof. Dr. Jorge Marx Gómez

    Wednesday: 10:00 - 12:00, weekly (from 03/04/19)

    Die Übungszeiten können sich noch ändern! Bitte sprechen Sie die Lehrenden an.

Exercises
  • No access 2.01.661 - Digitale Transformation Show lecturers
    • Christian Janßen, M. Sc.
    • Prof. Dr. Jorge Marx Gómez

    Wednesday: 10:00 - 12:00, weekly (from 03/04/19)

    Die Übungszeiten können sich noch ändern! Bitte sprechen Sie die Lehrenden an.

Hinweise zum Modul
Prerequisites

No participant requirements

Prüfungszeiten

After the end of the lecture period.

Module examination

Papers, project or written examination. Announcement at the beginning of the lecture period.

Skills to be acquired in this module

After successful completion of the lecture, the students should be able to define enabler and actors of a digi-tal transformation within the context of a model company. Furthermore, key competences such as Cloud Computing or IoT are used to make potential exploitation by new digital business models visible. The results will be evaluated. The lecture explains basic properties of a digital transformation for companies and shows specific develop-ment potential. By forming and building a model company, students are able to create a realistic and practical scenario. A final documentation reveals the degree of fulfilment and the students point ov view on the scenario.
Professional competence
The students:

  • recognize basic properties and facts of a digital transformation for companies
  • devide different terms of digital transformation
  • expose actual introduction projects
  • compile practical knowledge by dividing goals of enabler and acteurs of a digital transformation
  • obtain basic knowledge of key competences such as IT-Security, Data Analytics, Big Data, Cloud Computing
  • identify digital business models within the specific development potential

Methodological competence
The students:

  • etermine and analyse required information
  • prepare the given information for specific target groups
  • destablish an analytical understanding of digital enterprise structures within key competences and applications

Social competence
The students:

  • work in groups, identify work packages and take on responsibility for the jobs assigned to them
  • discuss and introduce the results on a functional level

Self-competence
The students:

  • reflect their actions on the basis of self defined objectives
  • analyse their own state of knowledge

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