Introduction to Data Visualisation
Large datasets can be difficult to understand when viewed as rows of values alone. Visualisation makes important information easier to notice, helping people explore data, focus attention and communicate findings clearly. However, its value depends on presenting the data accurately and designing the visual with a clear purpose and audience in mind.
Technique Overview
Introduction to Data Visualisation Definition
Data visualisation is the graphical representation of data using visual forms such as charts, graphs, maps and diagrams. It translates data into a format that helps people identify comparisons, patterns, trends and relationships more efficiently. Effective visualisation is purposeful: its design should reflect the data being presented, the task being completed and the needs of the intended audience (Munzner, 2014; Kirk, 2024).
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Business Evidence
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Further Reading
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Introduction to Data Visualisation references (4 of up to 20) *
- Cleveland, W.S. and McGill, R. (1984). Graphical Perception: Theory, Experimentation, and Application to the Development of Graphical Methods. Journal of the American Statistical Association, 79(387), pp.531–554. doi:10.1080/01621459.1984.10478080.
- Correll, M. (2019). Ethical Dimensions of Visualization Research. Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems. doi:10.1145/3290605.3300418.
- Franconeri, S.L., Padilla, L.M., Shah, P., Zacks, J.M. and Hullman, J. (2021). The science of visual data communication: What works. Psychological Science in the Public Interest, [online] 22(3), pp.110–161. doi:10.1177/15291006211051956.
- Kirk, A. (2024) Data Visualisation: A Handbook for Data Driven Design. 3rd edn. London: SAGE Publications Ltd.
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