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Storytelling With Data: How Not To Make Bad Data Visualization Choices

Storytelling With Data: How Not To Make Bad Data Visualization Choices

Ambika Choudhury

We have written extensively about Data Visualisation in the past and BI tools have been playing a crucial role in the present day businesses and management domains. By understanding the strengths and weaknesses of BI tools, one can gain the ability to use it in a proper manner. In this article, we list a few pointers to help you get a clearer vision of the do’s and don’ts of data visualisation.

Do’s Of Data Visualisation

Always Consider The Purpose Behind The Visualisation

Before diving into the visualization process, one must understand the main purpose or goal behind creating the visualisation. It is crucial to understand what kind of visualization one must use to represent the specific project. There are mainly two kinds of visualization, one is the presented visualization and the other is the distributed visualization. The former focuses on key highlights while the other focuses on both contexts as well as the conclusion.

Do Understand To Use The Correct Visualisation And Choose The Most Effective One

There are various kinds of data visualization tools for various specific problems and you have to an understanding and knowledge to use the appropriate visualization for the particular project. Different types of visualization include treemap, circle packing, parallel coordinates, slope graphs, etc. For instance, in this 3D bar chart, it is difficult to understand the height of each bar as well as the values in the rear dimensions. Also, to gain an in-depth of the different visualisation tools, click here.

Keep The Visualization Simple

Good data visualizations should have the power to message by making the data points simple and easy to understand. A complex graph and infographic will make more people difficult to understand the message that the graph wants to show. Simple t effective graphs like pie-charts, bars, etc. grab attention to the viewers and help to make them understand the reasonable points behind it.

Always Highlight The Important Pieces of information

It is crucial to make sure that the labels are aligned in an appropriate way and are not crowding the important data on the graph. Highlighting the important points will emphasise the particular data that you want to show to the people. Size and color make attraction to the eyes so it is to make sure that the color contrast, sizes, and positions are placed consciously.

Don’ts Of Data Visualisation

Don’t Use Too Many Colors For Visualization

Yes, different colors help us understand any visualization in a fast manner but when it is used too much, it no longer helps us to understand anything rather creates confusion and complications while visualizing the data. It is better to hold minimum color shades in order to lessen the perplexity.

See Also
Pygal Visualization Tutorial

Don’t Use Erratic Scales

It is said that excess of anything is bad. In the same manner, if a visualization consists of too much inconsistent scales it can create confusion in understanding the result behind it. However, it is not forbidden to use multiple variables in a single visualization but one must have the proper knowledge of using the way of it.

Avoid Misrepresentation Of Data Which Leads To Misleading Graphs

Misrepresentation of data leads to misleading the person who wants to understand the data and the purpose. The cases can be improper labelling of a graph, data is left out, etc. For instance, this is a real-life example of a bar chart is a misleading graph because we can see a huge difference between the two bars but when we focus on the y-axis, we see that the graph begins from point 34 instead of 0 which means the  difference is not huge or double but it is just around 4%.

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