Once accurate and complete, insights need to be easy to share and easy to understand. Data visuals must inform the mind, awaken the imagination and inspire you to take action. You need to choose the right type of journey you want to take your audience through.
"Human brains process visuals 60,000 times faster than they do text." (University of Minnesota)
Five easy steps to create rigorous and beautiful data visuals
Long story short: You need to know the right amount of information to include in your visual and avoid producing stunning visuals with hard to decipher messages. Be clear if you want to show a relationship, comparison, distribution, evolution, hierarchy, or data composition, abide by the technical principles and make it look impressive.
Step 1: Kick-start your thoughts
First, you need to choose the right form of data representation. How you approach your data has a lot to do with how much data, how many categories, and how many variables you need to showcase. To kickstart your thoughts, one of the best approaches is sketching. Sketch, draw, doodle, draw arrows, connections, curves, chart simulations, and everything that will allow you to grasp what you have, how it lays out, and what is missing. Andrew Abela published a Chart Chooser Cheat Sheet in his Extreme Presentation Method. Please take a few moments to examine it full-size on this link.
(c) based on A. Abela's Chart Chooser, 2010, full-size.
Step 2: Prepare your data
After choosing the right form of representation, you need to prepare the data for a seamless generation of your data visualization. You need to check that your data is complete, accurate, and laid out in the right way to express your data vision visually. Check your data against the following attributes:
- Importability (making it easy to be imported)
Step 3: Sit down & execute your visual
Next, you need to go more in-depth on this process and make sure you do a proper job in terms of execution. Each chart type comes with a handful of guidelines, best practices, and pitfalls that may either make it a good choice for your particular data set or send you back to the drawing board.
You may do your own research, or access the Interactive Chart Chooser by Depict Data Studio which is fully packed with valuable information and most importantly, lots of guidelines on making sure you make correct and judicious use of each chart. For execution, depending on who needs to read the visual, and how they interact with it, you have a wide array of options that will position your visual as simple or complex, static or interactive, technical or editorial.
Besides nimble use of Microsoft Excel, which with a couple of design tweaks, is still a fast and reliable option, you may also use tools like Raw Graphs or the Graph Maker Tool from Canva to produce your visuals quickly. To make the most out of interactivity you will need to go with more technical-savvy options like Tableau or D3Js. On the more editorial side, to make beautiful visuals you may need to use graphic design tools like Adobe Illustrator.
Step 4: Abide by the following data information design principles
- Get familiar with the complete anatomy of basic charts. Enable yourself to apply fundamental design principles to complex dashboards, interactive visualizations, and even data art.
- Avoid misleading charts and include all necessary apparatus (guides, scales, overlays, footnotes) but no clutter.
- Make sure your percentages add up to 100% if they should. If they don’t, tell us. Inform the audience about the absolute numbers those percentages are based on.
- Choose the right angle, framing, and focus on your visualization. Decide if you want to explain, exhibit, or encourage your audience to explore.
- Always encode your data accordingly. Make sure your visualization looks impressive and is easy to read. Having stunning visuals but a hard to decipher message defeats the purpose.
- Define the mood, tone, and feel of your data design.
Step 5: Learn, play and stay genuinely curious
Having a playful attitude, genuine curiosity, and always exploring ways to visualize data definitely pays off. Most data professionals only become curious about data visualization when they encounter a challenge or work-related obstacle and soon lose interest afterward. You may get familiar with data visualization, get inspired, and stay ahead of the curve by following publications that are known to showcase great visuals (e.g. The New York Times, The Guardian, Vox), follow data visualization resource-rich websites (e.g. Visual Capitalist, Visualising Data, FlowingData), or use neat and useful resources that you may physically have at hand at your office like the Chart Chooser Cards and templates. These are playful and interactive ways to generate the right data visualization with little effort.