Analysing and Visualising Data (CS)
| Course unit title | Analysing and Visualising Data (CS) |
| Course unit code | 800101022405 |
| Language of instruction | English |
| Type of course unit (compulsory, optional) | Elective |
| Teaching hours per week | 30 |
| Year of study | 2026 |
| Number of ECTS credits allocated | 3 |
| Name of lecturer(s) | Heidi WEBER |
| courseEvent.detail.semester | |
| Degree programme | Computer Science |
| Subject area | Engineering Technology |
| Type of degree | Master full-time |
| Type of course unit (compulsory, optional) | Elective |
| Course unit code | 800101022405 |
| Teaching units | 30 |
| Year of study | 2026 |
| Name of lecturer(s) | Heidi WEBER |
Basic knowledge of MS Excel
According to the current status, MS Excel and Power BI on a Windows operating system are required for the exercises.
Time slot: 1 October to 19 November 2026, on Thursdays from 6 pm (1 Oct., 5 Nov., 12 Nov. and 19 Nov. in presence, 8 Oct., 15 Oct., 22 Oct. and 29 Oct., virtually)
Course language: English
Course occupancy: Minimum 9 persons / Maximum 21 persons
Course costs: None
Sustainability: SDG 4 - understanding data; SDG 8 - sustained economic growth
FHV Future Skills: Appropriate Application, Focus on Information Literacy, Enhance Communication Skills
Registration: From 1-10 June 2026 in A5 under ‘Course selection’. If a late booking is required, please contact sabine.frick@fhv.at.
• Strategies for data and analysis
• Data and data structures
• Using MS Excel with PowerPivot for data analysis
• Using PowerBI for data analysis
• Creation of dashboards
• Designing data visualisations for specific target groups
• Presenting complex data correlations
Students learn that a strategy is needed to use data properly. They can ask the right questions to be able to get relevant answers from the data. They know how to identify the information that is relevant for decisions in the organisation or in their personal lives.
Students are able to acquire, evaluate and prepare digital data from their own organisation and from external sources.
They know how simple data models are created and can understand data structures with multiple tables.
They are able to create data analyses in Microsoft Excel and Microsoft Power BI.
They will be able to create simple dashboards in Power BI.
They will be able to visualise data and adapt it for goal-oriented presentations to a specific target group.
Impulse lecture, exercises, discussion.
Later: Teamwork on concrete, self-selected challenges.
Project work and presentation.
For further questions please contact: heidi.weber@fhv.at
Heath, C., & Starr, K. (2022). Making Numbers Count: The art and science of communicating numbers. Bantam Press.
Heesen, B. (2024). Effective strategy execution: Business intelligence using Microsoft Power BI (Third edition). Springer. https://link.springer.com/book/10.1007/978-3-662-68807-6
Hichert, R., Faisst, J., & Association, M. of the I. (2026). International Business Communication Standards (IBCS Version 2.0): Compose compelling business reporting based on ISO 24896 notation. IBCS Media.
Knaflic, C. N. (2015): Storytelling with data: A data visualization guide for business professionals. Wiley.
Richardson, D. T. (2026). Advanced Microsoft Power BI Guide: DAX, Data Modeling, Power Query & Dashboard Design for Business Analysts. Independently published.
Four of the eight lectures are in-class, and four (sessions 2 to 5) are online lectures.