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Course info
FES / ADAM
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Course description
Department/Unit / Abbreviation
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FES
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ADAM
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Academic Year
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2023/2024
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Academic Year
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2023/2024
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Title
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Data Modelling
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Form of course completion
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Examination
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Form of course completion
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Examination
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Accredited / Credits
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Yes,
10
Cred.
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Type of completion
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Combined
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Type of completion
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Combined
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Time requirements
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Lecture
12
[Hours/Semester]
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Course credit prior to examination
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No
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Course credit prior to examination
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No
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Automatic acceptance of credit before examination
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No
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Included in study average
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NO
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Language of instruction
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English
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Occ/max
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Automatic acceptance of credit before examination
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No
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Summer semester
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0 / -
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0 / -
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0 / -
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Included in study average
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NO
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Winter semester
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0 / -
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0 / -
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0 / -
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Repeated registration
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NO
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Repeated registration
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NO
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Timetable
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Yes
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Semester taught
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Winter + Summer
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Semester taught
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Winter + Summer
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Minimum (B + C) students
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not determined
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Optional course |
Yes
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Optional course
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Yes
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Language of instruction
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English
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Internship duration
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0
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No. of hours of on-premise lessons |
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Evaluation scale |
S|N |
Periodicity |
každý rok
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Periodicita upřesnění |
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Fundamental theoretical course |
No
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Fundamental course |
No
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Fundamental theoretical course |
No
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Evaluation scale |
S|N |
Substituted course
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None
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Preclusive courses
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N/A
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Prerequisite courses
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N/A
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Informally recommended courses
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N/A
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Courses depending on this Course
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N/A
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Histogram of students' grades over the years:
Graphic PNG
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XLS
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Course objectives:
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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.
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Requirements on student
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-
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Content
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Aspects of data relevance.
Data and functional modeling, methods and tools.
Abstract programming.
Data modeling approaches, blending of approaches.
Linkage of data and process modeling.
Identification of data indicators for monitoring and evaluation.
Development trends in public administration organizations.
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Activities
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Fields of study
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Guarantors and lecturers
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Literature
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Basic:
Modeling with UML.
(Rumpe, B.)
( DOI: https://link.springer.com/book/10.1007/978-3-319-33933-7 )
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Basic:
Resource Management for Big Data Platforms.
(Pop, F., Kołodziej, J., Martino, B.)
( DOI: https://link.springer.com/book/10.1007/978-3-319-44881-7 )
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Recommended:
Main Memory Management on Relational Database Systems.
(Alvarez, P. M., Ayala, M. L., Cisneros, S. O.)
( DOI: https://link.springer.com/book/10.1007/978-1-4471-4866-1 )
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Recommended:
Hills, T. NoSQL and SQL Data Modeling.. 2016. ISBN 978-1634621090.
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Prerequisites - other information about course preconditions |
- |
Competences acquired |
The student will be able to apply data modeling methods and in connection with process modeling methods, will be able to choose appropriate techniques and tools for data modeling of business processes, will model data indicators for monitoring and evaluating quality and performance. |
Teaching methods |
-
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Assessment methods |
-
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