Semester:WS 20/21
Type:Module
ECTS-Credits:3.0
Scheduled in semester:3
Semester Hours per Week / Contact Hours:30.0 L / 22.5 h
Self-directed study time:67.5 h
Type:Module
ECTS-Credits:3.0
Scheduled in semester:3
Semester Hours per Week / Contact Hours:30.0 L / 22.5 h
Self-directed study time:67.5 h
Module coordination/Lecturers
- Prof. Dr. Pavel Laskov
(Modulleitung)
Curricula
Master's degree programme in Information Systems (01.09.2019)Events
Description
Data Visualisation covers techniques for creating effective data visualisations based on principles from statistics, cognitive science, and graphic design to help analysts and decision-makers understand and explore big data. The course covers eight primary topics:
- Visualising univariate and multivariate numerical data
- Visualising time series data
- Visualising geospatial data
- Visualising networked data
- Visualising high-dimensional data
- Visualising textual data
- Interactive dashboards
- Animations
Learning Outcomes
After successful completion of the course, students will:
- understand the main concepts, theories, and methods of data visualisation
- recognise the typical challenges of visualising large and complex data sets
- be able to create graphs like bar charts, scatterplots, line charts, and heatmaps to represent various types of data sets visually
- be able to use data-visualisation methods to analyse business problems, generate possible solutions, and compare these solutions in terms of their effectiveness and efficiency
Qualifications
Lectures Method
- The course involves interactive lectures with exercises to integrate theoretical knowledge with practical design and analysis skills.
- The e-learning platform Moodle is used throughout the course to disseminate course material and for information and discussion.
- Real-life examples are used to show how the course content can be applied in practice.
Literature
- Compulsory reading:Cairo, A. (2016). The Truthful Art: Data, Charts, and Maps for Communication. US: New Riders.