Are you someone who needs to tell a convincing story to an audience? Are you are data journalist or a data analyst? Then you know that data storytelling is an art form. There is not a set of rules or methodologies that work in all cases. There are some best practices however. You want your stories to be compelling and free from false narratives.
Data storytelling is communicating the meaning of a data set with visuals and a narrative that are customized for each particular audience. A narrative is another word for a story. Storytelling is still, after all these years, the most natural form of education. As a side note, a parable is a story that compares. That’s because stories make learning easier by helping us process and remember information. Stories help with our understanding and recall. Human brains automatically organize events with a beginning, a middle, and an end. The story should connect the data you’ve collected to the project objective and clearly explain important insights from your analysis. Stories evoke empathy and emotions. Here are the three (3) C’s of
Data Storytelling Steps:
- Context – Engage your audience. First, know your audience
- Challenge – Create compelling visuals.
- Conclusion – Tell the story in an interesting narrative
What is spotlighting? Spotlighting involves scanning through data to quickly identify the most important insights. This can be done with notes on a whiteboard, by searching for broad ideas, and by identifying concepts that arise repeatedly. Spotlighting involves scanning through data to quickly identify the most important insights. This can be done with notes on a whiteboard, by searching for broad ideas, and by identifying concepts that arise repeatedly.
Key Parts of the Story
According to the Google Analytics Certificate course, the five key parts are character, setting, plot, big reveal, and the aha moment.
According to Joshua Smith at the LinkedIn website, the five key elements of data storytelling are setting (situation), characters, conflict (problem, challenge or opportunity), plot (fit together) and theme (decision, take-away). Themes make slideshows more consistent and professional by controlling color, font types and sizes, and positioning of text and visuals.
In a Forbes article by Brent Dykes called Data Storytelling: The Essential Data Science Skill Everyone Needs, it said the following: “Data storytelling is a structured approach for communicating data insights, and it involves a combination of three key elements: data, visuals, and narrative.” The article describes the intersection of these three, using Venn diagrams. When narrative and visuals are merged together, they can engage or even entertain an audience. When narrative is coupled with data, it helps to explain to your audience what’s happening in the data. When visuals are applied to data, they can enlighten the audience to insights that they wouldn’t see without charts or graphs. When all three are combined, we can affect change.
Framework
The purpose of a framework is to create logical connections that tie back to the business task. It also gives your audience context about your data and helps you focus on the most important information.
An initial hypothesis is a theory you’re trying to prove or disprove with data. You want to establish your hypothesis early in the presentation
Learn from TED
Here is a video definitely worth watching called How your brain responds to stories — and why they’re crucial for leaders. For data to truly resonate with people, you need a good story to go with it. Your entire brain starts to light up when you listen to a story. Emotions and empath come into play. The more empathy you experience, the more oxytocin is released in your brain, which causes you to view the storyteller as more trustworthy. Just telling a good story makes people trust you more. Data doesn’t change a person’s behavior, but emotions do.
A good story keeps you engaged and in anticipation of what is going to happen next. A good story has a surprise. Data alone never speaks for itself. Our brains love to anticipate the story. Our own background and bias will fill in the gaps of the story unless we are guided through the story. A great story answers three questions.
- What is the context? Setting? Who? Why should I care?
- What is the conflict?
- What is the outcome? Moral of the story.
A good story builds and releases tension over and over. A good story will change you.
The questions to guide your data story include: Who? What? Why? and How?
Learn from Tableau
Tableau’s website has a article (whitepaper) called 5 best practices for telling great stories with data.
Five important data storytelling considerations that apply to all of your data stories (not in any specific order).
- comparisons
- rank ordering
- trends over time
- relationships
- counter-intuition