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Data Visualization: A New Trend for Industries

Why is data visualization such a powerful tool for industries? Ironically, you can thank your prehistoric ancestors for the skill in identifying and deriving meaning from visual patterns at the heart of modern data visualization tools. Just as our ancestors learned to key in on subtle visual cues that suggested the presence of predators, prey or competitors, so too do today’s data scientists use visualization to uncover patterns and trends that might otherwise go unnoticed until too late.

While we’ve long understood the value of data visualization – think of how often you’ve heard phrases such as “A picture is worth a thousand words” or “Show, don’t tell” – it’s only with the advent of powerful analytics tools that the cost of entry to deep data visualization has gotten to the point where it’s accessible to enterprises of virtually all sizes. Today, data visualization tools ranging from simple dashboards to impactful infographics to powerful analyses suites help enterprises in virtually every industry make better and more informed decisions more quickly than ever before.

Some common examples of data visualization tools include:

  • Tables – While most people don’t think of the humble table as a form of data visualization, the way it imposes context on data is one of the simplest forms of data visualization. Even balance sheets are a basic form of data visualization and retain value even in a 3-D and full-color world.
  • Charts – There are innumerable forms of charts, from the classic sales line chart through area charts, pie and donut charts, bar charts and other, more exotic forms. Each has their benefits and limitations, but they tend to be of most value when data points need to be compared with each other.
  • Plots – Plots are useful in showing the relationship between data points, especially when variables are involved. For instance, a “spaghetti plot” can visually present the varying outcomes of different inputs or models, such as with storm tracks. A scatter plot helps identify trends and outliers by graphing data points on two or three axes. A spectrum plot can show where something lies – such as consumer purchase intent – in between two ends of a defined range.
  • Treemap – Treemaps are useful for identifying the components that make up a whole, usually displaying them as different sized rectangles within a single border. They’re powerful in utilization review, time management, cost containment and other analyses of how a defined resource is being utilized.
  • Heatmap – Heatmaps are best used to show a visual representation of aggregate behavior or probability. They can help identify everything from where in-store shoppers are spending the most time to where on a website users are most likely to click.
  • Maps -- One of the most famous early uses of what we would now consider to be data visualization was in 1854, when British physician John Snow plotted the homes of patients in a cholera outbreak onto a map of London’s water mains, using that to identify a particular contaminated water pump behind the disease’s spread. For many enterprises, visualizing the interaction of your data with the real world through a map can lead to valuable, and often surprising, insights.

Interested in learning about what data visualization best practices look like for your industry, and how you could see your existing data in a new way? Contact us to find out more.


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