The Three Elements of Successful Data Visualizations Source: HBR.orgNow that we've discussed when data visualization works — and when it doesn't , let's delve into what makes a successful data visualization. Although there are a number of criteria, including ease of comprehension and aesthetics, I'd like to explore the three that designers most often overlook.

1. It understands the audience.
Before you throw up (pun intended) data in your visualization, start with the goal, which is to convey great quantities of information in a format that is easily assimilated by the consumers of this information — decision-makers. A successful visualization is based upon the designer understanding whom the visualization is targeting, and executing on three key points:

Who is the audience, and how will it read and interpret the information? Can you assume it has knowledge of the terminology and concepts you'll use, or do you need to guide it with clues in the visualization (e.g., indicated good is up with a green arrow)? An audience of experts will have different expectations than a general audience.
What are viewers' expectations, and what type of information is most useful to them?
What is the visualization's functional role, and how can viewers take action from it? An exploratory visualization should leave viewers with questions to pursue; educational or confirmational visualizations should not.

2. It sets up a clear framework.
The designer needs to ensure that everyone viewing the visualization...

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GE Digital

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GE Digital connects streams of machine data to powerful analytics and people, providing industrial companies with valuable insights to manage assets and operations more efficiently. World-class talent and software capabilities help drive digital industrial transformation for big gains in productivity, availability and longevity. We do this by leveraging Predix, our cloud-based operating system, purpose built for the unique needs of industry.