What is Data Visualization?

One of the most useful tools available for presenting complicated material in an accessible way is data visualization. This rapidly evolving field is focused on using visual representations like graphs or charts to convey raw data. Presenting data in a visual manner makes it easier to understand and faster to process, even for those who aren’t mathematically inclined or trained in analytics. These visual representations of data aren’t just visually appealing, they also tell a story about the information, allowing audience members to spot outliers, notice trends, and see patterns emerge from data. Visually conveying points is a powerful way to leverage data in order to achieve the desired outcome.

There are many kinds of data visualizations, each of which serves a specific professional purpose. Some of the most popular techniques for conveying information are:

  • Histograms
  • Waterfall charts
  • Area charts
  • Scatter plots
  • Infographics
  • Maps
  • Pie charts
  • Bar charts
  • Box-and-whisker plots
  • Heat maps

Because we live in an increasingly visual culture, those who know how to present information in visually engaging stories have the power not only to help make sense of past events but to offer predictions for the future as well.

This article will explore the important role storytelling plays in creating compelling data visualizations.

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How Storytelling is Used in Data Visualization

Data is at the heart of business operations and decision-making. Having the tools to leverage data can help an organization in a number of ways. Data provides a means to tell a story that can provide support for a position or underscore why a service or product has value. However, raw data alone cannot do this work. No audience member wants to receive a stack of spreadsheets containing thousands of rows and numbers to understand what is important and what action is needed. Instead, a more engaging way to convey information is needed. This is where storytelling comes in.

Data-driven storytelling is a powerful and effective means of communicating numerical data to an audience. It involves breaking down bare data and incorporating various narrative elements to help ground the facts. In order to do so, data visualization techniques such as images and charts are applied to depict the meaning of the data in a relevant and engaging manner. Data Analysts wishing to tell a data-driven story must begin by analyzing and filtering extensive datasets so that they can find new avenues into understanding the information.

When a writer pens a novel, they must consider certain key components of effective storytelling. Data-driven storytelling requires some of the same sensibilities. Those working to create data stories should consider:

  • Audience: Before an effective story can be told, it’s important to define the audience it is intended to reach. Knowing who will read and view a data story is crucial, as it dictates what kind of story you will tell and how best to tell it. Just like in fiction, where there is a difference between writing a children’s book and an adult crime novel, the way data stories are presented depends on what audience they are trying to reach, and what this audience already knows about the topic at hand.
  • Plot: What questions are you hoping to address in the story? How do you propose answering them? How will you guide the audience to the desired conclusion? Effective data stories provide the scaffolding to help the audience efficiently move from point A to point B.
  • Setting: In data stories, setting pertains to the context you provide to the audience to help them interpret data. Some examples of creating setting in data stories involve industry benchmarks and historical data.
  • Characters: All good stories need characters with whom the audience can relate. Who are the stakeholders this data affects? What are their priorities, their goals?
  • The end: An important aspect of a successful data-driven story is the conclusion it reaches. Just like in a novel, most readers approach a story anticipating how it will end. The ending of data stories is similarly important. Effective endings generally provide a conclusion that is congruent with the topic at hand. They may also include a brief summary of what the audience learned from the story, how results can be achieved, and what actions could be taken to lead to better future outcomes.

Tips for Effective Storytelling

There are many benefits to using data storytelling to communicate important information:

  • Since all data storytelling revolves around numbers, any claims that you make can be anchored to numerical facts. This helps the audience trust what you are presenting.
  • Because data stories provide a larger context of meaning to the data being presented, the audience can fill in blanks and transform numbers into actionable insights that will lead to action.
  • We live in a visually-driven culture. Graphic components of data stories not only are appealing to those within an organization but can also gain the attention of media channels. This means that data stories that are especially well-constructed can be picked up by publications or other high-profile influencers, which can help reach a larger audience.
  • When storytelling is enhanced with interactive visualization techniques, audience engagement is further piqued. Interactive elements are helpful in storytelling because they can be used to help guide the audience to the aspect of the data that’s most pertinent to their needs or help them to reach a desired conclusion.
  • When visual and narrative components are combined into a story, both sides of the brain are activated in audience members. They view the information emotionally and analytically, which leads to greater comprehension and retention.
  • Data stories serve many purposes. They can be included in various internal and external communications, like brochures, case studies, annual reports, websites, videos, and social media.

Data-driven storytelling in Tableau or other data visualization platforms is a powerful tool to help convey important information to an audience. Many organizations already use this technique to help break down dense, complex data into a visually driven story that is engaging and effective. In the future, it is expected that more organizations will devote funding and resources to help train Data Analysts and others working with data to be able to weave visual stories from large datasets. Those who have the power to tell a compelling story have the power to win an audience and affect the outcomes of an organization.

Hands-On Data Visualization Classes

Are you interested in learning more about how to create stunning and helpful data visualizations? If so, Noble Desktop offers Tableau classes that prepare students to work with this industry-standard data visualization software.

Noble Desktop’s data analytics classes are open to students with no prior coding experience. These full-time and part-time courses are taught by top New York Data Analysts and provide timely and hands-on training for those wishing to learn more about topics like Python, SQL, Excel, or data science, among others. In addition, Noble’s live online data visualization courses are designed for students who prefer learning in the virtual format.

In addition, Noble Desktop’s Classes Near Me tool is designed for those who want to locate other data visualization courses in the area. These courses provide training for those who are new to working with data, as well as those with prior experience who hope to perfect their data visualization skills.