Data visualization is the representation and presentation of data to facilitate understanding. By using visual elements like charts, graphs, and maps, data visualization tools provide an accessible way to see and understand trends, outliers, and patterns in data.
Data is names, amounts, groups, statistical values, dates, comments, locations. Data is textual and numeric in format, typically held in datasets in table form, with rows of records and columns of different variables.
Data representation: to derive understanding from data we need to see it represented in a different, visual form.
Presentation: beyond presentation choices, the presentation of data concerns all the other visible design decisions that make up the overall visualization anatomy.
(Kirk, 19-21)
Some data visualizations are exploratory in that they are created before any analysis is done on the data. Looking at a visual representation of our dataset can give us clues about what to focus on during analysis.
Some data visualizations are communicative in that they are created in order to present our analysis findings to an audience. Using visual patterns to represent patterns in data can be an effective way of explaining complex results.
Ultimately, data visualizations can more effectively answer questions, tell stories and put forth arguments than words alone.
Kirk, Andy. Data Visualization. Sage: 2016.
Tableau. Data visualization beginner's guide: a definition, examples, and learning resources. https://www.tableau.com/learn/articles/data-visualization
Few, D. (2013). Data Visualization for Human Perception. https://www.interaction-design.org/literature/book/the-encyclopedia-of-human-computer-interaction-2nd-ed/data-visualization-for-human-perception
Kirk, Andy. Data Visualization. Sage: 2016.