Course: Computerized Data Processing

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Course title Computerized Data Processing
Course code MUSKM/2PZD
Organizational form of instruction Lecture
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)
  • Urbánek Tomáš, Ing. Ph.D.
  • Kunčar Aleš, Ing.
Course content
The basic rules and principles of working with data: key concepts, design and creation of data structures, relationships, acquisition, editing and storage of data, data security, etc. Obtaining information and data analysis: calculations and functions, sorting, simple and advanced filtering, subtotals, pivot tables, etc. Evaluation and presentation of outcomes: forms, reports, charts, pivot charts, exports, etc. Effective evaluation and increasing of productivity: the choice of optimal instruments for the task, automation of evaluation, control objects, definition of terms, etc.

Learning activities and teaching methods
Lecturing, Monologic (Exposition, lecture, briefing), Exercises on PC, Practice exercises
  • Preparation for course credit - 62 hours per semester
  • Home preparation for classes - 16 hours per semester
  • Participation in classes - 10 hours per semester
learning outcomes
Knowledge
Defines key concepts of data analysis
Defines key concepts of data analysis
Explains the concept of data processing
Explains the concept of data processing
Clarifies the difference between distinct types of database systems
Clarifies the difference between distinct types of database systems
Describes the principle of creation a relational database
Describes the principle of creation a relational database
Clarifies the difference between spreadsheets and database systems
Clarifies the difference between spreadsheets and database systems
Skills
Imports data from an external source
Imports data from an external source
Creates a chart in the MS Excel
Creates a chart in the MS Excel
Summarizes data using a pivot table or graph
Summarizes data using a pivot table or graph
Creates a relational database
Creates a relational database
Decides which type of query to use for data analysis
Decides which type of query to use for data analysis
teaching methods
Knowledge
Lecturing
Monologic (Exposition, lecture, briefing)
Monologic (Exposition, lecture, briefing)
Lecturing
Exercises on PC
Exercises on PC
Practice exercises
Practice exercises
assessment methods
Analysis of the student's performance
Grade (Using a grade system)
Grade (Using a grade system)
Analysis of the student's performance
Recommended literature
  • Barilla. J., Simr, P., Sýkorová, K. Microsoft Excel 2016: podrobná uživatelská příručka. Brno: Computer Press, 2016. ISBN 978-80-251-4838-9.
  • Belko, P. Microsoft Access 2013: podrobná uživatelská příručka. Brno: Computer Press, 2014. ISBN 978-80-251-4125-0.
  • Laurenčík, M. Excel - pokročilé nástroje: funkce, makra, databáze, kontingenční tabulky, prezentace, příklady. Praha: Grada, 2016. ISBN 978-80-247-5570-0.
  • Laurenčík, M. Excel 2016: práce s databázemi a kontingenčními tabulkami. Praha: Grada, 2017. ISBN 978-80-271-0477-2.
  • MacDonald, Matthew. Access 2007 [elektronický zdroj]. Farnham : O´Reilly,, 2007. ISBN 978-0-596-52760-0.
  • MacDonald, Matthew. Excel 2007 [elektronický zdroj] : the missing manual. Sebastopol, CA : Pogue Press/O´Reilly, 2007. ISBN 978-0-596-52759-4.
  • NAVARRŮ, Miroslav. Excel 2019: podrobný průvodce uživatele. http://www.grada.cz/excel2019. Praha: Grada Publishing, 2019. ISBN 978-80-247-2026-5.
  • Pecinovský, J. 333 tipů a triků pro Microsoft Excel 2013: [sbírka nejužitečnějších postupů a řešení]. Brno: Computer Press, 2014. ISBN 978-80-251-4130-4.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester