Previous Post (Part 2 of 3): A Tale of Four Quadrants

We started this series by introducing the notion of a two dimensional plane on which to assess all data graphics, and then followed it up with an example of visualizations in four different quadrants on the plane to illustrate the differences between the two axes, clarity and aesthetics, that define the plane.

Now, let’s review some of the basic principles & tips that you will find in the data visualization resources out there. All I have done here is I have applied these well-known best practices to the four quadrant system. Those of my readers who are familiar with the field of data visualization will recognize these tips – they are not new. Those who aren’t: please take careful notes, for the good of us all!

Before showing the three tips, I want to make one thing very clear: as the designer of a data graphic, you are not the audience. Your audience is the audience. As obvious as that may sound, I often have to remind myself of this fact. After working for hours on end with a data set, you have certain truths about that data set in the front of your mind that your audience likely will not. Before publishing anything, it always helps to ask different potential audience members (1) what they notice, (2) what they like and don’t like, and then pay attention to (3) what they don’t notice. This isn’t a compliment fishing session – truthful friends are the best kind.

Without further ado:

Tip #1 – First, avoid confusing your audience with the wrong chart type.  Clarity is the cake.

Tip #2 – Second, avoid horrifying your audience with poor design elements. Aesthetics are the icing.

Tip #3 – Third, incorporate helpful elements to increase both clarity and aesthetics. The best dessert has both.


I’d love to know what you think about these tips, and what you would add, change, or take away. What did you find to be a great tip that isn’t included here?

I hope this 3 part series was interesting & enlightening for you – I know it was helpful for me to put together and consolidate my key learning points from the great resources that are out there, and the experts who have created them. I also hope that the four quadrant system I have proposed here gives you a way of thinking about data visualizations that serves to move your work north and east!

Lastly, and to summarize: “Clarity is the cake. Aesthetics are the icing. The best desserts have both.”

Thanks for stopping by, as always,