Challenges in Data Visualization

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That’s the challenge in Data Visualization.

The first thing to keep in mind is that you will work with a huge amount of information and data set, not just only 4 or 5 pieces of information.

1️⃣ Selecting proper visual metaphors

The choice of graph, colour or even chart junk is the factor you should take into consideration when you start working on the design.
However, before you consider those things, the accuracy of the data is the thing to take care of first. You have to be careful once you work with the number. If you truly understand the accuracy of statistics, you will be able to present it in a way that is able to deliver a specific meaning or insight.

2️⃣ Legibility without too much reliance on legends and labels

One thing to note when it comes to refining your visualization is not to make your users keep referring constantly to the legend. It is fractured in the eyes when they have to move around to check what information is presented. The best practice is the information should be understood by just looking at the graphic.

Try to keep the design clean and minimalist and avoid the eyes movement to the legends back and forth. Source

Symbology is one of the interesting factors that could help you to handle with visualize a cluster of information.

This map uses a controlled colour palette, tonal value and different variations in size.
This design approach conveys pretty well the comparative relationships and density. When we look at this, we know which areas provide higher education and which ones are not. Besides, this map also tells us that there is a link between poverty and education.

3️⃣ Data density and credibility

Cartographers often have to create high-density visualizations. Source: https://pro.europeana.eu/post/maps-for-makers-famous-cartographers

What is Data density? Data density refers to the large sample set of data within a statistical graphic. Our eyes can detect fine differentiations in tone, line widths and shapes within a small space, thus people can see large amounts of information in a single graphic.