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

  
Degree programme:Contextual Studies
Type of degree:Intern
 Special-Time
 Winter Semester 2023
  

Course unit titleData Visualisation and Analytics
Course unit code800101022404
Language of instructionEnglish
Type of course unit (compulsory, optional)Elective
Semester when the course unit is deliveredWinter Semester 2023
Teaching hours per week2
Year of study2023
Level of course unit (e.g. first, second or third cycle)First Cycle (Bachelor)
Number of ECTS credits allocated3
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: https://www.overdrive.com/search?q=E7164763-7B23-48A5-B44D-A1C03174B4DE (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.

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