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Data Visualization Principles (Part II)

4 months ago - Laura Lundell

Continued from Part I, using the visualization principles from Storytelling with Data: A Data Visualization Guide for Business Professionals, by Cole Nussbamer Knaflic using Stack Overflow Developer Survey, 2017 data in Excel.

Now that we've removed the clutter, we will put in the finishing design touches to really make sure our data is telling the story we intended, clearly and concisely.

4) Focus attention where you want it

You are an artist-- an artist with a story to tell. You can focus the audience’s attention wherever you please using visual tools to your advantage.

Knaflic introduces the concept of “preattentive attributes” and their ability to effortlessly direct our audience to specific information. A few of these attributes include include color, position, and size. We want to stress the lowest and highest earnings for survey respondents who earned a bachelor’s or master’s degree, so we put them in ascending order.

preattentive attributes

Using preattentive attributes

Here, because both bar are equally important and size indicates relative important, we will keep them the same size. However, we want to use color to differentiate the two. The goal is to use color consistently (to signify association between components of the visual) but sparingly (cognitive overload warning).

5) Think like a designer

Good design flies under the radar.

“But I’m not a designer,” you say. If we consider data visualization to be the intersection of science and art, then good design is just part of the artistic process. Remember that humans are programmed to react to aesthetics just as much as the information at hand. With a few key considerations, good design is attainable and your visual will reap the rewards.

An important consideration in the design process is the use of affordances. How intuitively will the viewer be able to see and interact with the visual? Often, these elements of visual design fall under the preattentive attribute category, as they unconsciously direct the viewer’s attention to specific pieces of data in strategic ways by highlighting the most important pieces.

  • Use boldface, italics, and underlining, our audience can immediately see what is most important. Knaflic recommends using minimal underlining as it can distract attention rather than direct it effectively.

  • When color is used sparingly, any change in color is even more effective in highlighting important information and minimizing distraction. What is less important? Show this by fading the color or using gray.

design attributes

Using design attributes

Here, we want to highlight the degree paths most commonly associated with the tech profession so choosing shades of gray for the other fields achieves this mission.

When people see aesthetically pleasing designs, it’s perceived to be easier to use, regardless of whether or not it is. Use this to your advantage so your audience is set up well to take action and the goals you set out to achieve can be accomplished.

6) Tell a story

Now we come full circle. The story you tell depends on the answers to our initial questions: Who is this for? What is my relationship with them? What action will they take or what conversations might be started using this information?

You want to create a visual not only to convey information but more importantly, convey meaning. The graph shows there is a difference in earnings not only for specific degree holders but also whether that degree is a Bachelor’s or Master’s. How do we interpret it? How or why is it different? Keep the story simple and communicate with your audience in mind; remember, the story is for them.

Adding text invites the audience to see the nuances into the story, behind all the data. It creates meaning and context which is far more powerful in communicating the need for change or conversation than numbers alone.

Stories are capable of uniting an idea with an emotion. How should the audience feel when they see it? What emotions do you want to convey?

storytelling with data

Telling a story

Ask yourself, “Am I telling the story I intended to tell? Am I telling a story that connects with my audience?”

In this updated graph, we want to accent the difference in earnings between Bachelor’s and Master’s degree holders who work as professional developers in the US. We can bring out specific information from the data for our audience to consider, showing that tech degrees not only are shown to have a higher overall salary but also that a Master’s degree can prove to be more powerful when it comes to earning potential.

Ask for feedback from others on this, as doing it alone won’t be nearly as productive. However, be careful to remain authentic in the process of storytelling and not to edit so much that you cut out meaningful pieces that might create bias.

We have used Excel to communicate in a clear and visually appealing way because it comes with more plenty of customization tools for our needs-- to communicate the way we think is best for our audience. Throughout the process, be sure you are seeking feedback from your peers and audience. And remember good storytelling takes time. Time to craft, time to develop, time to get feedback and time to edit.

Just remember the steps:

  1. Understand the context (ask good questions!)
  2. Choose an appropriate visual display (consider the purpose)
  3. Remove the clutter (borders, gridlines, data markers, axis labels, color)
  4. Focus attention where you want it (where is attention drawn?)
  5. Think like a designer (data visualization = science + art)
  6. Tell a story (context, nuances, meaning)

Following these basic principles, there are endless ways to show and tell your data in meaningful ways suitable for your intended audience. Knowledge truly is power when it is presented in clear, concise, and aesthetically pleasing ways.

Here’s to influencing future change in relevant, data driven ways.

Check out the Storytelling With Data Podcast or take part in a #SWDChallenge starting again July 1.

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