Big Data, Data Science, Data Analytics. There are so many buzzwords, what distinguishes these fields, few people understand. While few realize the intricacies of these fields, we recognize and identify them from their common goal – better understanding. Enter, Data Visualization.
Data Visualization takes the insights gained from data and constructs a story. Like any story, a good visualization engages the audience, provides context, and reaches a climax while delivering a theme. But most importantly, to create a good story, there must be motivation. In data visualization, this motivation often comes in the form of a question. Sometimes this is a specific question, maybe through research of business requirements. Other times, it can simply be ‘why?’
Below, we will look at a visualization and discuss how each element was used to construct a story. As football season is just beginning, let’s look back at the 2015-2016 NFL season and the offensive and defensive performance of all of the NFL teams.
Engage the Audience:
The first goal is to capture the attention of the intended audience. To do this, it is important to both define and understand this audience. Once this audience is defined, interests and motivations become apparent, playing to these is essential for capturing attention in that initial engagement.
To provide value, a visualization has to answer questions. Above, we used the title to specify the question we are answering. With the title ‘What Makes an NFL Playoff Team?’ anybody that has an interest in any NFL team, or even football in general, will most often become engaged.
There are still many more ways to more effectively engage your audience. Utilizing color schemes or relevant shapes or logos is another way to gain interest. There is no better example than sports to show how easily people identify with particular colors.
Create context:
It is also important to keep any visualization simple and clean. Ideally, every element of a visualization should have a distinct purpose. Too much clutter can intimidate or confuse the reader. Above, we even eliminated traditional legends. By placing the Playoff Team and Not in Playoffs directly where the info is relevant, it allows for quicker interpretation and doesn’t force the reader to keep referring to the key.
By placing the key within the visualization, not only have we made it easy to quickly identify what each color represents, but we also are using the placement of the text to highlight the relationships the data is showing. We can quickly see that playoff teams are more on the left and teams that didn’t make the playoffs are on the right (more on this later).
But who is in the middle? Some teams hug this invisible wall, and some teams even appear to be on the wrong side. These teams will be more scrutinized than most, so we added the label for these teams only. A label for every team would be too much. By using labels selectively, we both highlight the important information and keep our visualization clean.
Reach Climax & Deliver Theme:
So why are playoff teams on the left and the other teams on the right? Because to make the playoffs in the NFL, defense matters. The fewer yards the defense allows, the more likely the team is to end up in the playoffs. We have asked a question and led the reader to the answer. The visualization does not directly give a recommendation but seeks to show information. By utilizing different elements to highlight this relationship, we have quickly informed the reader. There are many decisions where this information could be relevant, but the visualization does not go about making these decisions. Success means we have given relevant information to the people that need it, and they use this information to make informed decisions.
Notice that we have provided this information from data with essentially no math or number crunching – Data visualization is truly an art. The small details are often what makes a visualization stand out – it is not always the story, but how you tell it that makes it impactful.
