Course: Data Modelling

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Course title Data Modelling
Course code FES/DDAMI
Organizational form of instruction Lecture
Level of course Doctoral
Year of study not specified
Semester Winter and summer
Number of ECTS credits 10
Language of instruction Czech
Status of course Compulsory-optional
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Šimonová Stanislava, doc. Ing. Ph.D.
Course content


Learning activities and teaching methods
Monologic (reading, lecture, briefing), Dialogic (discussion, interview, brainstorming), Laboratory work
Learning outcomes
The aim of the course it to acquire theoretical knowledge, methods and principals of data modelling issues, particularly for application in terms of performance and efficiency improvement of enterprise processes.
Students are led to independent work on project development of the subject matter. Students will acquire knowledge which will use for their doctoral dissertation.
Prerequisites
unspecified

Assessment methods and criteria
Oral examination, Home assignment evaluation, Self project defence

Completion and successful defense of project from the field of dissertation work.
Recommended literature
  • Coronel,C. Database Principles - Fundamentals of Design, Implementation, and Management. Andover Cengage Learning EMEA, 2013.
  • Kirchmer, H. High Performance Through Process Excellence ? From Strategy to Execution with Business Process Management. Heidelberg Springer-Verlag, 2011.
  • Teorey, T., Lightstone, S., Nadeau, T., Jagadish, H. Database modeling and design. 2011.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester
Faculty: Faculty of Economics and Administration Study plan (Version): - (2014) Category: Economy - Recommended year of study:-, Recommended semester: -
Faculty: Faculty of Economics and Administration Study plan (Version): Informatics in Public Administration (2014) Category: Economy - Recommended year of study:-, Recommended semester: -