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How To Effectively Display Data Using These 5 Tips

We live in a data-dense world. From the constant barrage of emails, tracking every calorie we intake or burn, to monitoring every rise and dip in our financial portfolio; regardless of where we go or what we are doing, the consumption of data in various forms never stops. With a constant stream of data flowing around us, it is important that we make displaying our own data relevant and effective. Here are a few tips you can use to effectively display data:

Effectively Display Data | Creative Data Analysis

Maintain Credibility

In a time where we find ourselves surrounded with the concepts of "fake news" and "alternative facts", it is more important than ever to maintain integrity and impassivity when displaying information. The process of "shaping data" and "creative data analysis" are a sure way for your audience to lose faith in what you are showing them. When building your visualizations, don't forget:

If you torture data long enough, it will confess- Ronald Coase, economist

Always let the data speak for itself, your job is to give it a voice. Communicate what is there as truthfully and clearly as possible.

Avoid "Chartjunk"

"Chartjunk", a term coined by statistician Edward Tufte, refers to the use of superfluous items within our graphics or visuals that are unneeded and often a distraction. When building your visuals, it is important to think about the reasons for doing things like adding different gradients, boxed, lines, and typefaces. If these things aren't part of the story behind your data, when why are they there? The following is an example of chartjunk through unnecessary use of gradients:

ChartJunk | Effectively Display Data


Second Look

If you've ever worked on a project only to find that once you've delivered it to the client, that what you've given them ends up not addressing their true need, then you know the importance of this step. An effective design doesn't mean that a visual is complex, in fact, it's just the opposite. When you're nearing the end of your design process, show what you have developed to someone else. Ask them to tell you what the data is showing them. This is a great exercise to help you make sure that you aren't over complicating your visualizations. A good understanding of your content means you can strip the useless jargon and show only what matters.

Details Matter

One of the most easily overlooked items to any visual, and one of the most important in helping you maintain simplicity in analysis, is how you use details. Consider the visual below:

Creative Data analytics

The table of data gives us a list of materials, number of defects and total downtime. Now ask yourself, what is the most important purpose of this visual and what action might I be asked to take after seeing this? Currently the items are sorted alphabetically by material name, however, if this were sorted instead by Total Defect Qty or Total Downtime Minutes, the person viewing this could instantly see which items were causing the most issues instead of having to dig through the visual to find what they're looking for. Always consider the purpose of what you've chosen to show.

Never Underestimate The Audience

Don't fall into the trap of data visuals regarding the philosophy that "less is more". When displaying data, content is king. That doesn't mean that visualizations need to be overly complex, but we need to get away from the notion that people who consume our data visuals are somehow unable to process a large amount of information. Simplify your content, and give the viewer enough of it to make it worthwhile.

If you can't explain it simply, you don't understand it well enough- Albert Einstein

An excellent example of this to keep in mind is that of Google maps. When viewing maps, we see a large amount of simplified data; road names, buildings, restaurants, parks, water, etc. The audience is smart enough to be able to comb through this information and find what they're looking for. The two main things that Google Maps uses to help facilitate this are simple annotations, and the use of light colors to preserve details in their visuals.

By keeping these things in mind when working to display your own data, you'll be well on your way to making each visualization more impactful and meaningful to everyone viewing them.

Topics: shaping data creative data analysis effectively display data