Course: Corporate Data Analysis and Visualisation II

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Course title Corporate Data Analysis and Visualisation II
Course code KMA/AVD2
Organizational form of instruction Seminary
Level of course Bachelor
Year of study not specified
Semester Summer
Number of ECTS credits 3
Language of instruction Czech
Status of course Compulsory, Compulsory-optional
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Zimová Štěpánka, Ing.
  • Škvor Jiří, RNDr. Ph.D.
  • Loukotová Lucie, Mgr.
Course content
unspecified

Learning activities and teaching methods
unspecified
Learning outcomes
Prerequisites
unspecified
KI/ICT
----- or -----
KI/ZZD

Assessment methods and criteria
unspecified
Recommended literature
  • Dokumentace a manuály k programu Qlik Sense.
  • Barilla, J., Simr, P., Sýkorová, K. Microsoft Excel 2016: podrobná uživatelská příručka. Brno: Computer Press, 2016. ISBN 978-80-251-4838-9.
  • Demel, J. Operační výzkum.
  • Fotr, J., Švecová, L. Manažerské rozhodování: postupy, metody a nástroje. Praha: Ekopress, 2016. ISBN 978-80-87865-33-0.
  • Lukáš, L. Pravděpodobnostní modely v managementu: Markovovy řetězce a systémy hromadné obsluhy. Praha: Academia, 2012. ISBN 978-80-200-1704-8.
  • Lukáš, L. Pravděpodobnostní modely v managementu: teorie zásob a statistický popis poptávky. Praha: Academia, 2012. ISBN 978-80-200-2005-5.
  • Pour, J., Maryška, M., Novotný, O. Business intelligence v podnikové praxi. Praha: Professional Publishing, 2012. ISBN 978-80-7431-065-2.
  • Skalská, H. Stochastické modelování. Hradec Králové: Gaudeamus, 1998. ISBN 80-7041-039-6.
  • Zimola, B. Operační výzkum. Zlín: Univerzita Tomáše Bati ve Zlíně, 2014. ISBN 80-7318-208-4.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester
Faculty: Faculty of Science Study plan (Version): Information Sciences (double subject) (A14) Category: Informatics courses - Recommended year of study:-, Recommended semester: -
Faculty: Faculty of Science Study plan (Version): Information Sciences (double subject) (A14) Category: Informatics courses - Recommended year of study:-, Recommended semester: -
Faculty: Faculty of Science Study plan (Version): Information Systems (A14) Category: Informatics courses - Recommended year of study:-, Recommended semester: -