The Simple and Powerful Art of Data Visualization in Storytelling

Author: Staff

A profile of a man looking to the left with charts and data displayed on a screen behind him.

A major focus of the local news, especially during a snowstorm or a hurricane, is the weather forecast.

But what if the weather anchor sat behind a desk and talked about an approaching hurricane or a blizzard without using any visuals in the story?

Would it have the same impact as seeing the real-time path of a snowstorm or hurricane, or the color-coded rainfall amounts as hurricanes come on land?

When news teams use visuals to tell the story of weather data, viewers can see the impact and feel the sense of urgency about a serious weather event that weather data or words alone can’t accomplish.

The visuals humanize the story.

Making the Data Story Human

Notre Dame data science faculty, Dr. Jennifer Cronin, explained the importance of telling the story of the data in a way that decision makers can feel a personal, meaningful connection to the ideas being presented:

“Data scientists must be talented storytellers who can translate the insights uncovered in the data into actionable business outcomes that can be understood by non-technical decision makers. The most robust data and statistical analysis isn’t going to matter if you’re not able to communicate the impact of the data you uncovered in a compelling way.”

Data visualizations, such as charts, statistical graphics, plots, maps, and dashboards, are tools that enable data scientists to communicate their insights in meaningful and creative ways, so decision makers can grasp and understand difficult concepts and see new patterns.

This type of creativity in data science is an indispensable human element.

As Ryan Welsh, Notre Dame alumnus and the founder and CEO of Kyndi, described at our Palo Alto immersion:

“No matter how the processes of data science change or become automated, creativity and resourcefulness will always be in-demand.

Data Visualization: Simple and Powerful

Simple visuals, when used effectively, can enable data scientists to answer the questions like “what’s the point” and “why should I care;” in so doing, visualizations can make complex information accessible and meaningful to non-technical audiences.

As Jack Moore, Notre Dame alumnus and product manager at ZapLabs, highlighted in a corporate panel discussion at our immersion in Palo Alto:

“A lot of times it is hard to explain data science to people in layperson’s terms so I spend a lot of time thinking about how I can make data science not sound complicated, which can be really challenging.”

Data visualization takes complex findings and illuminates them in a way that creates “ah hah” moments that inform and engage internal and external audiences in the story of the data.

That’s not all.

Data visualization also allows you to recognize outliers and interesting patterns in data that would otherwise remain hidden in the rows and columns of data.

In his lecture at Notre DameHadley Wickham, the Chief Scientist at RStudio and the developer of ggplot2, a chart-making system for the programming language R that revolutionized data visualization, explained how data visualization can surprise you and show you something you did not anticipate.


Using Data Visualization in Storytelling

Dr. Matthew Sisk, GIS Librarian in the Center for Digital Scholarship, teaches data visualization. He shared these simple, yet effective tips for creating good visuals with data:

  1. Choose your colors carefully.
  2. Always attribute the source of the data used to create the visual.
  3. Make sure your visualization is relevant to the story you are trying to convey.
  4. Your visualization should get the point across to the audience.

The Power of the Dashboard

When a single graphic or visual is not enough to communicate complex insights, data scientists use dashboards to change a visualization as the viewer interacts with the narrative, explained Sisk.

To illustrate the power of a good dashboard that effectively uses an interactive map and multiple related visualizations to communicate insights gathered from complex health metrics, Sisk shared Ella Koeze’s FiveThirtyEight dashboard on 35 Years of American Death” chronicling the mortality rates for leading causes of death in every U.S. county.

The article examines demographic and epidemiological data to determine if where we live can predict how we die.

It opens with an interactive map that uses a color spectrum to show estimates of mortality across the country. In one glance, readers can see the regions with the highest and lowest rates of mortality in the U.S.  


Drilling down into the data, looking at the regional trends, a simple table lists the 20 counties or parishes with the highest mortality rates. A quick glance shows rural Appalachia stands out with nine counties in Kentucky and West Virginia on the list. The Dakotas are also heavily represented. The only use of color on the chart highlights the estimated deaths for each county in 2014.


In contrast, an identical table illustrates the 20 counties with the lowest mortality rates. Again, readers can quickly see states west of the Mississippi that are well-represented.

The data also shows the common causes of death over the last 30 years. Using a simple table that ranks the most to the least common deaths, readers can see that Americans are much more likely to die from cardiovascular disease than nutritional deficiencies. Yet, the table only depicts one part of the story. An orange trend line next to each cause of death on the list shows which causes are on the rise and which are falling. Readers can see in a quick glance that cardiovascular disease is falling and mental and substance abuse are on the rise.

Koeze’s article has all the requirements of a good dashboard.  

It uses simple, easily understood visuals to walk readers through the story of the data.

Straightforward maps and tables illustrate the regional variations in mortality.

The exceptional use of color in the graphics highlight the meaning of the data in a quick glance.

The visual layout of the dashboard throughout the narrative succeeds in making the complex simple.

Notre Dame Prepares Exceptional Data Storytellers

To prepare students to use data visualization effectively in data storytelling, Notre Dame’s online data science master’s program developed a course specifically designed to teach students the principles and skills of creating data-driven visuals that help viewers to find meaning in a sea of data.

Discover how Notre Dame’s online master’s in data science prepares students to be three-dimensional data scientists, who in addition to a strong quantitative and ethical foundation, also have the excellent communication and data visualization skills needed to connect the dots of a sophisticated data analysis for the decision-makers in their organizations.