Information on individual educational components (ECTS-Course descriptions) per semester

Degree programme: Master Business Administration: Accounting, Controlling & Finance
Type of degree: FH Master´s Degree Programme
Part-time
Winter Semester 2023

Course unit title Data Visualisation and Analytics
Course unit code 800101022404
Language of instruction English
Type of course unit (compulsory, optional) Elective
Semester when the course unit is delivered Winter Semester 2023
Teaching hours per week 2
Year of study 2023
Number of ECTS credits allocated Second Cycle (Master)
Number of ECTS credits allocated 3
Name of lecturer(s) Heidi WEBER


Prerequisites and co-requisites

Basic knowledge of MS Excel


Course content

    •    Strategies for data and analyisis
    •    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


Learning outcomes

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.


Planned learning activities and teaching methods

Impulse lecture, exercises, discussion.
 
Later: Teamwork on concrete, self-selected challenges.


Assessment methods and criteria

Immanent examination character
 
Active participation
 
Project work and presentation.


Comment

According to the current status, MS Excel and Power BI on a Windows operating system are required for the exercises.


Recommended or required reading

 
Bakhshi, Soheil (2021): Expert Data Modeling with Power Bi. S.l.: PACKT PUBLISHING LIMITED.
 
Cairo, Alberto (2019): How charts lie: getting smarter about visual information. Online im Internet: URL: www.overdrive.com/search (Zugriff am: 24.06.2022).
 
Ferrari, Alberto; Russo, Marco (2017): Analyzing Data with Power BI and Power Pivot for Excel. Redmond, Washington: Microsoft Press.
 
Heath, Chip; Starr, Karla (2022): Making Numbers Count: The art and science of communicating numbers. London: Bantam Press.
 
Knaflic, Cole Nussbaumer (2015): Storytelling with data: a data visualization guide for business professionals. Hoboken, New Jersey: Wiley.
 
 
 


Mode of delivery (face-to-face, distance learning)

Four of the eight lectures are in-class, and four (sessions 2 to 5) are online lectures.