Data visualization is representing data to show the statistical parameters of a data set, time series, or image that is intended to tell a story. Data visualization aims to facilitate the depiction and understanding of data to the intended audience. With data visualization, it is possible to show data in multiple ways to make it possible to find “possible stories” as well as data points that are of interest
The focus of a chart should be to entice readers to go deeper into the story, to achieve this, charts must be meaningful and draw the attention of the audience. According to Dougherty and Ilyanku some of the best practices to build data visualizations are:
Deconstructing charts by adding short, concise titles, showing the scale of both horizontal and vertical axes, and labels or small annotations to give more context
Providing a good sense of scale by having bar charts and column charts always starting at the zero mark, and pie charts adding up to 100%
Chart aesthetics should avoid junk by using only the necessary elements to make the chart readable and understandable. Removing junk means also removing distractions like unnecessary backgrounds, colors, or shadows
Color should always have a meaning; it should not be used to embellish the chart but to enrich its storytelling capabilities.
We must remember to always start with the audience and the reason why we want to share a message so we can create a powerful chart that conveys the most information possible. But remember, always try and keep it simple!
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