Eva Murray, who leads the Business Intelligence department at Exasol, believes in the power of story. “Stories are the common currency of humanity. Humans have used storytelling for thousands of years to share our history, to pass on and preserve information and to communicate important messages. When reality becomes complicated, stories offer the form, the chronology, and the simplicity that audiences need. Storytelling gives you the chance to build examples and experiences into your message and makes your message more relatable.”
In our continuing discussion about data visualization, let’s delve further into storytelling’s power to make data come alive.
The Elements that Create a Story
Data visualization becomes a form of storytelling when these three elements come together—data, narratives, and visuals. Each plays a unique and crucial role in communicating with an audience. When they are combined, they create a powerful, engaging, and memorable data-absorbing experience. And here’s why:
Data and narratives explain. Data and visuals enlighten. Narratives and visuals engage.
“Data by itself, just numbers, often leaves people scratching their heads. But when you create a good visualization that clearly shows the data and what it means, that is when you get an “Aha!” moment from your audience. They have been enlightened!” explains Nick Mannon.
Let’s begin with the basics.
- Strive for simple and digestible
Think bite-sized pieces of data designed for maximum impact. Think simple with the ability to make information quickly digestible. Strive for visuals that answer specific questions and induce effective strategizing.
Check out these tips from the Data Visualization Competency Center.
- Eliminate clutter
Be mindful of elements that take up space without increasing understanding. If too much clutter complicates the visual and therefore impedes understanding, the audience may lose focus as their attention wanders.
- Choose the right visual for the job
Emily Rugaber notes how best to utilize these graphics visualization tools. (See examples and additional types here.)
- Tables show one record per row, display a large amount of information, but may overwhelm users who are just looking for high-level trends.
- Line charts track changes or trends over time while displaying the relationship between two or more variables.
- Area charts are like line charts but with a shaded area below the line.
- Scatterplots show the values of two variables plotted along two axes, the pattern of the resulting points revealing any correlation present between them.
- Pie charts use wedge-shaped parts to compare parts of a whole. Rugaber advises the use of labels to note the exact proportion of each wedge clearly.
- Treemaps are great for comparing, in a space-efficient way, the proportions between categories via their area size.
Now, it’s time to tell the story.
“Imagine you have just watched a great and captivating movie with an excellent storyline. You got attracted by the story that took you on a memorable journey and eventually evoked an emotional response from you,” shares Admond Lee, Data Scientist, and Big Data Engineer. “Use stories to engage your audience emotionally in a way that goes beyond what facts can do.”
Remember that the purpose of each storytelling narrative is to communicate a story that resonates with the audience. Create a simple, authentic narrative that gives “a face, a name, a persona” to the data and addresses this audience’s specific need to absorb this data.
“The story is not for you; the story is for them,” reminds Lee. For gaining further insight into the use of storytelling, Lee recommends the book, “ Storytelling with Data: A Data Visualization Guide for Business Professionals” by Cole Nussbaumer Knaflic.
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