Course detail

Visualisation of Business Data

FP-vbdPAcad. year: 2026/2027

The course focuses on practical skills in data visualization, which are essential for the effective presentation and interpretation of business information. The course is conducted through computer-based instruction.

Students will become familiar with various data visualization tools, such as Tableau and Power BI, and will learn the basic principles of effective visualization, including working with charts, colors, and design. Additionally, the course will cover data collection and preparation, the creation of both basic and advanced visualizations, data analysis and storytelling, the development of dashboards and reports, integration with other tools, optimization of visualization performance, and the ethical and security aspects of working with data.

Language of instruction

Czech

Number of ECTS credits

3

Mode of study

Not applicable.

Guarantor

Ing. Jiří Kříž, Ph.D.

Department

Institute of Informatics (ÚI)

Entry knowledge

Prerequisites include a basic understanding of working with data and basic computer skills.

Rules for evaluation and completion of the course

Conditions  for Graded Credit:
The student must obtain at least 50% of the points during the semester, i.e., 50 points out of 100.
Plagiarism or unauthorized collaboration on projects or tests will result in the credit not being awarded and may lead to disciplinary proceedings.
Midterm Test: Completion of a practical task according to the assignment (40 points). The minimum number of points is 20.
Project: One project according to the assignment with the appropriate documentation (60 points). The minimum number of points is 30.
The assignment is presented in the third lecture. The evaluation is in accordance with the ECTS grading scale.

Course Completion for Students with Individual Study PlansCredit Conditions:
Completion of a project according to the assignment with the appropriate documentation. The assignment is presented in the third lecture.
A minimum of 50 points out of 100 is required. 

Aims

The aim of the course is to equip students with practical skills for creating effective and interactive visualizations, enabling them to better understand and present business data.

Study aids

Study supports are displayed in e-learning.

Prerequisites and corequisites

Not applicable.

Basic literature

FEW, Stephen. Information Dashboard Design: Displaying Data for At-a-Glance Monitoring. Analytics Press, 2013. ISBN 978-1938377006. (EN)
KNAFLIC, Cole Nussbaumer. Storytelling with Data: A Data Visualization Guide for Business Professionals. Wiley, 2015. ISBN 978-1119002253. (EN)
WEXLER, Steve, SHAFFER, Jeffrey a COTGREAVE, Andy. The Big Book of Dashboards: Visualizing Your Data Using Real-World Business Scenarios. Wiley, 2017. ISBN 978-1119282716. (EN)

Recommended reading

SLEEPER, Ryan. Practical Tableau: 100 Tips, Tutorials, and Strategies from a Tableau Zen Master. O'Reilly Media, 2018. ISBN 978-1491977316. (EN)
TUFTE, Edward R. The Visual Display of Quantitative Information. Graphics Press, 2001. ISBN 978-0961392147. (EN)
YAU, Nathan. Visualize This: The FlowingData Guide to Design, Visualization, and Statistics. Wiley, 2011. ISBN 978-0470944882. (EN)

Classification of course in study plans

  • Programme BAK-MIn Bachelor's 3 year of study, winter semester, compulsory-optional

Type of course unit

 

Exercise

26 hours, compulsory

Teacher / Lecturer

Ing. Jiří Kříž, Ph.D.

Syllabus

1. Introduction to Data Visualization (course overview and objectives, basic concepts and the importance of data visualization, Introduction to data visualization tools (e.g., Tableau, Power BI))
2. Basic Principles of Data Visualization (types of charts and their uses, principles of effective data visualization, working with colors and design)
3. Data Collection and Preparation (data sources and acquisition, data cleaning and transformation)
4. Working with Data Visualization Tools (installation and basic setup of tools, importing data into tools, basic operations and functions)
5. Creating Basic Visualizations (bar, line, and pie charts, working with tables and matrices, interactive elements)
6. Advanced Visualizations (heatmaps, scatter plots, and geographic maps, combining different types of charts, advanced interactive elements)
7. Data Analysis and Storytelling (basic methods of data analysis, interpretation of results, creating stories from data)
8. Dashboards and Reports (designing and creating dashboards, working with filters and parameters, exporting and sharing reports)
9. Integration with Other Tools (integration with databases and cloud services, automating data updates, APIs and scripting)
10. Case Studies and Real Projects (analyzing real data sets, creating visualizations for specific business problems, presenting results)
11. Optimization and Performance (optimizing visualization performance, working with large data sets, best practices)
12. Ethics and Data Security (ethical aspects of data visualization, data privacy protection, security measures)
13. Final Project and Presentation (working on the final project, presenting projects to the class, feedback and evaluation)

Self-study

38 hours, optionally

Teacher / Lecturer

Ing. Jiří Kříž, Ph.D.

Individual preparation for an ending of the course

16 hours, optionally

Teacher / Lecturer

Ing. Jiří Kříž, Ph.D.