Courses Master Display 2019-2020

Course Description To PDF
Course title Data visualisation
Course code EBC4225
ECTS credits 5,0
Assessment None
Period
Period Start End Mon Tue Wed Thu Fri
5 15-4-2020 7-6-2020 X X
Level Advanced
Coordinator Bram Foubert
For more information: b.foubert@maastrichtuniversity.nl
Language of instruction English
Goals
This course is an introduction to the field of Data Visualization. Students will learn the fundamentals of data visualization. We will study different visualization methods and discuss how they can be used to visualize and explore quantitative datasets effectively. We will evaluate several approaches and learn how human perception interprets visualized data in various different ways.
Description
In the last decade, big data became an integral part of our economic and social life. This trend was heavily influenced by the technologically capabilities to store and collect data (Computing power, IoT, Cloud Computing, broadband expansion) and the increasing digitilization of social interactions (e.g. Facebook, Twitter, Instagram). Improved technologies are making it possible to process the resulting data sets efficiently and effectively as the potential revenues are in many cases higher than the costs (Olshannikova et al, 2015). This leads to an exponentially growth of the total amount of available data that can be used within industry and business , while the ability to analyze these data increase at much lower rate (Keim et al 2008). The result is that the (proper) use and the ability to correctly interpret data is playing an increasingly important role (Russom, 2013). The improvement of the human ability to manage data, extract information and gain knowledge from it is of vital importance in this context (Olshannikova, 2015). Visualization is an effective way to enhance the human capabilities to extract and interpret information as also to support human decision making.
In this course students will learn the fundamentals of data visualization. We will study different visualization methods and discuss how they can be used to visualize and explore quantitative datasets effectively. We will evaluate several approaches and learn how human perception interprets visualized data in various different ways.
Literature
* Course book
* Lecture slides
* Academic papers and readings
Prerequisites
There are no formal prerequisites.
Keywords
Teaching methods PBL / Lecture
Assessment methods Final Paper / Participation / Assignment
Evaluation in previous academic year For the complete evaluation of this course please click "here"
This course belongs to the following programmes / specialisations
Master Business Intelligence and Smart Services Core Course(s)