What Is Data Visualization?

Data visualization is the representation of information in a visual format (source). Visualizing data takes accumulated information from across an organization and presents it in a chart, graph or other image that allows anyone to recognize a trend or shift, and the reasons behind the trend or shift. Any patterns within the visualized data are much easier to spot than when poring over text- or numeric-based documents.

Exponential amounts of data are generated every moment by businesses around the world—aka Big Data. This massive influx of data demands technology and tools capable of analyzing it, giving the stories it tells vibrant life and making critical assessments possible.

Why Data Visualization Works

The human eye is naturally drawn to color and shape; the brain to recognizable patterns. Not only can we differentiate between colors, but we can also infer meaning from them. Culture, at its core, is visual. Everywhere you look, artists, marketing teams, and movie and television producers create renditions that spark interest and keep the viewer not just entertained but engaged.

Have you ever opened a mammoth Excel sheet and either tried to make sense of it to no avail or immediately lost interest? Huge blocks of textual explanations or numerical representations of data can quickly extinguish an attention span regardless of interest in the subject matter. But offer the same information in a color-coded chart, and the information that words and numbers can only attempt to convey becomes tangible. This is the power of data visualization.

Types of Data Visualization

The term data visualization likely conjures images of a chart—remember those bar graphs you made in school? This is data visualization at its most basic. When you have two sets of data—number of sales and time range, for instance—bar graphs are a simple way to visually show “We sold X number of hats in December.”

But what makes data visualization so spectacular, especially in the days of Big Data, is that it lets you show how many red (blue, green, and yellow) hats, scarves, gloves, sweaters and coats you sold for December this year, December last year, December the year before that, and how your Decembers look compared to November or January.

The most important aspect of visualizing data, though, is that you pair the right visual images with the right datasets. For instance, if symbolizing something beneficial, you wouldn’t necessarily use the color red, and you wouldn’t present an intricate message of several years’ worth of connected data using a simple pie chart. Data visualization has evolved into an effective data presentation method you can be creative with.

The most common data visualization types include:

• Maps
• Charts
• Infographics
• Bar graphs
• Platform dashboards

The evolution of data visualization has enabled:

• Bubble clouds
• Bullet graphs
• Heatmaps
• Matrices
• Timelines
• Treemaps

One of the best examples of data visualization dates to the late 18th century—Joseph Priestley compiled world history from over 100 locations and spanning from around 1150 BC to 1789 AD. His New Chart of History remains one of the most compelling visualizations of data ever created.

Why Using Data Visualization Is Important

Can you think of an industry that wouldn’t see the advantage of understandable and relatable data? All STEM fields require understanding information—but so do financial organizations, marketing teams, SaaS providers, education professionals, and shampoo companies. Data visualization fills a practical hole in these and many other industries, and its applications in the real world are unquestionable, making visual communication a highly prized skill. Professionals who can relay important product testing data visually have a much better chance of leveraging the information they’re sharing.

Requested skills for positions throughout the business world are evolving to include data manipulation and visualization skills. The world is so driven by data, you could say it is the axis on which the business world turns. Traditional degrees have always drawn a line between the creative and the technical—between telling a story and analyzing facts. Data visualization skills in today’s business world are the crossroads of these very different disciplines.

How to Create an Engaging Data Visualization

Wondering how you can make your presentations, infographics, and other data visualizations pop? How to take potentially drab and boring information and create a dynamically interesting presentation that appeals to anyone from sales to the C-suite?

When done well, your data projects will tell a story without you saying a word—they can even bring to light important information that may otherwise have gone unnoticed.

Before delving into specifics, like elements, colors, fonts and such, bring the point of your visualization into sharp focus by defining what this visualization needs to accomplish. This helps you nail down the data needed.

To do this, consider the following:

• Who the audience is
• What questions the audience has
• What answers your data might provide
• How to frame the narrative of the data
• What additional questions or conversations the data may spark

Once you know the above, you’re ready to create a data visualization with a clear, intended message that tells your audience an illustrated, easy-to-digest story, and leaves them with helpful, actionable insights.

Some final tips:

• Use the right type of visualization for the data you’re presenting.
• Patterns represented should be predictable and easy to follow.
• Use colors to vibrantly tell your story.
• Text should be intentional, add to the story, and not detract attention.

If you’d like to learn more about data visualization, reach out and speak with one of our experts today.