BD-2-004 (0) - Visual Analytics

• Big data analytics 2016 - Big data analytics
• Big data analytics 2017 - Big data analytics
• Big data analytics 2018 - Big data analytics
• Big data analytics 2019 - Big data analytics
• Big data analytics 2020 - Big data analytics
• Big data analytics 2021 - Big data analytics - specialised professional studies
• Big data analytics 2022 - Big data analytics - specialised professional studies
• Big data analytics 2023 - Big data analytics - specialised professional studies

2 (2023-10-23 till 2023-12-31)

Engelska

Obligatorisk

Högre yrkeshögskoleexamen

1

5 sp

Aim of this course is to equip students with
the background knowledge to create visual
presentations that effectively support human
cognition by transforming raw data into
actionable insights and knowledge.

Knowledge
By the end of this course, students should
understand the main principles of good data
visualization and be able to apply them
effectively. Students are also expected to
identify, differentiate, and create the most
common chart types, as well as justify their
visualization choices.

The students learn how to lead in turbulent
times through data driven management. The students
also learn to understand how to become an agent of
change for transforming data into insights.
People are often visual beings and therefore
the focus of the course is on reducing
information, through algorithms, that can then be
visualized.
The students develops an understanding of
visual analytical methods as a communication
medium for business intelligence.

None

Hans Rosling,
https://www.ted.com/talks/hans_rosling_shows_t Extern länk
he_best_stats_you_ve_ever_seen#t-1171606

Juuso Koponen, Jonatan Hildén, Data
visualization handbook, Aalto ARTS Books (2019)

Tamara Munzner, Visualization Analysis and
Design, CRC Press (2014)

Alberto Cairo, The functional art : an
introduction to information graphics and
visualization, New Riders cop. (2013)

Colin Ware, Information visualization :
perception for design, Morgan Kaufmann (2013)

Närundervisning

Assignment 1: Critique and improve
Students need to critique a ?bad? chart and
create a new version, which should also
incorporate at least one new data set to
provide more context to the original data.

Assignment 2: Final assignment
The final assignment will be similar to last
year?s, but will focus more on the design
side.
Students should follow Munzner?s framework
when
creating their assignment and need to
convincingly explain their (design) choices
and
decisions.

• Scherbakov-Parland Andrej
• Westerlund Magnus
• Dayama Niraj

Westerlund Magnus

https://arcada.itslearning.com/ Extern länk

Ingen begränsning (40 studenter anmälda)

12 månader efter kursens slutdatum

2023-10-09 till 2023-11-05