![]() I think that this principle is something that you should apply to data viz. I use to do some popular science writing, where I had to take an academic research paper and write it in a style that a 8-year old could understand. If you take one thing away from this blog, it is that simple is good. I hope these three points help you design your vizzes in a simple and effective way. Imagine if the line chart was labelled instead of coloured, would it be as powerful? Here is another example of how colour can be used to highlight fields in the view. That is where I want the reader to look, so I use colour to draw their eye there. It is instantly clear what Malta is doing relative to other countries, and the increase in the bar chart is even more evident due to the colour. Try to keep colour to a minimum and think about if you need it or not? Take the example above, I use red, the colour of Malta, to identify it in the chart. ![]() Yet using too much achieves the opposite. ![]() If you use monochrome, the eye is not dragged anywhere. How the brain reads colour is incredibly interesting, and I recommend you to read up on it if you want to take your visualisations seriously. It is perhaps more important than the viz itself. Draw the reader into your story, and tell them something useful. If everything is crammed into the view then your eye is constantly being dragged around. Give those charts some room, using blank layout containers and text boxes so that they can achieve their full potential. I use to take the approach of trying to find lots of information in a dataset and then present all of it in one go. And keep the number of charts to a minimum. Look at the example below, it is clear to you without knowing anything about the subject matter what I want to tell you through the viz. I like to use a question as my title, that way the reader knows what the subject matter is and the relevance to the viz. A title should both inform the reader of what they are looking at, as well as leading them towards something in the graphic. It is where the reader looks first and we all know how important first impressions are. But a simple and clear title is essential to a successful dashboard. You may think of a title as an afterthought. But is it effective? Let’s have a look at some best practices when it comes to planning and structuring your viz. And yes, Tableau art as I like to call it will stand out. If someone can’t understand your viz within 5 seconds, they will move on. In the modern world of twitter, your viz will appear in a flood of others, especially with Makeover Monday. A chart or dashboard should stand out and be obvious to the reader. I don’t want to post images or name names, but hopefully a lesson in simplicity can help improve peoples visualisations. However, what is it telling me? This blog post came about after watching the Makeover Monday viz review on Wednesday. I often see work on Tableau public and particularly through Makeover Monday which is visually stunning, however misses the point. I have always taken this approach to my visualisations, check my Tableau public gallery to see. If you see a viz and don’t know what it’s message is in 5 seconds, then (in my opinion) it hasn’t done its job. Simplicity is key to any good visualisation. Let’s have a look at how to apply it to our world of work. ![]() Something which is easily transferable to data visualisation. I forget who it was in particular who introduced me to the acronym, but I thank you whoever you are! Essentially, it boils down to not over complicating things. KISS – this is a principle I have come across in past work and life in general before joining The Data School and entering the world of data analytics.
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