Data storytelling has become an essential skill for communicating insights from data analysis. As data continues to grow in volume and complexity, the ability to craft compelling narratives and visuals from data is highly valued across many industries. Whether you’re looking to improve business presentations, create engaging dashboards, or convey research findings, learning the fundamentals of data storytelling can help you get your message across more clearly and effectively.
What is data storytelling?
Data storytelling involves using data to communicate information in a meaningful way. It goes beyond simply presenting numbers and charts to weave data into an insightful, engaging narrative. The goal is to connect with your audience on an emotional level and help them understand the significance of the data through contextual story elements.
Effective data storytelling typically involves the following elements:
- Establishing a clear, focused narrative – What’s the key message or insight you want to convey?
- Contextualizing the data – How does this relate to the audience or business goals?
- Using compelling visuals and presentations – Charts, graphs, images that bring the data to life.
- Crafting a logical flow and structure – Organize content in a natural progression.
- Drawing meaningful conclusions – What actions or decisions does this lead to next?
By combining data analytics skills with creative storytelling techniques, data storytellers can produce content that informs, enlightens, and mobilizes audiences to action.
Why is data storytelling important?
In today’s data-driven world, the ability to communicate data-based insights effectively is more crucial than ever. Here are some of the key reasons why data storytelling has become so important:
- Making data accessible and engaging – Raw data alone can be dry, overwhelming or difficult to interpret. Storytelling makes data meaningful to wider audiences.
- Humanizing data – Stories add context and emotion to hard numbers. This helps build understanding, memory and connection.
- Persuading with data-driven narratives – Stories can influence hearts and minds more deeply than facts and figures alone. Data stories can be highly persuasive.
- Inspiring action from insights – Compelling data narratives motivate audiences and spur smarter decisions or changes.
- Democratizing data – Data storytelling helps share insights across organizations and with external stakeholders.
In a data-saturated world, storytelling is what converts passive information into active knowledge that engages audiences on a profound level.
What are the elements of effective data storytelling?
Great data storytelling artfully weaves together narrative, visuals and data. Here are some key elements that can help you craft more powerful data stories:
Clear narrative flow
Shape your story with a compelling narrative arc – establish the topic and stakes upfront, build rising action and tension, then resolve with conclusions and recommendations. Use storytelling devices like scenes, characters and dialogue to engage your audience.
Memorable visualizations
Charts, graphs and infographics should enhance the story visually. Use compelling visuals that distill data clearly and offer impact. Remember less is more – avoid overcrowded or distracting designs.
Concise language
Economize words for maximum impact. Use simple, crisp language and steer clear of jargon. Let data visualizations do the heavy lifting in conveying numbers. Focus language on bringing insights to life.
Audience perspective
Know your audience and their concerns. Craft the narrative to resonate with their objectives and motivations. Make the story relatable and useful to them.
Story before data
Lead with the key insights and story. Use data to substantiate the ideas, not overwhelm. Data should support the narrative rather than detracting from it.
Cinematic elements
Incorporate cinematic storytelling techniques: Establish scenes, introduce heroes and villains, inject drama and conflict, climax with resolutions. This builds engagement through emotion.
Strategic use of multimedia
Use multimedia like images, video, animation and audio to make stories more immersive. But ensure multimedia enhances rather than distracts from the narrative.
Call to action
Conclude with a clear call-to-action – what should the audience think, feel or do next? Solid conclusions motivate audiences to apply insights.
What are some data storytelling best practices?
Here are some best practices that can elevate your data storytelling skills:
- Know your audience – Tailor the story format and style to resonate best with your target readers or viewers.
- Lead with insights – Hook audiences by highlighting meaningful conclusions upfront.
- Show don’t tell – Let visual data and narratives do the explaining.
- Use captivating visuals – Memorable charts, images and videos are more persuasive than text.
- Humanize your story – Help audiences relate through real-world examples and characters.
- Craft your story arc – Structure the narrative strategically with a beginning, middle and end.
- Emphasize emotion – Appeal to your audience’s hearts, not just minds.
- Simplify complex data – Distill into understandable, digestible nuggets.
- Optimize for your medium – Tailor data stories for the intended channels or platforms.
- Iterate and improve – Refine your data stories through feedback and testing.
By focusing on audience, narrative and Design Thinking, you can develop captivating data stories that deliver true impact.
What tools can you use for data storytelling?
A range of helpful tools exist today for crafting rich data narratives. Here are some top options:
Data Visualization
- Tableau
- Microsoft Power BI
- Qlik
- Google Data Studio
- D3.js
- Highcharts
- Datawrapper
These visualization tools help build dynamic, interactive charts, graphs and dashboards to bring data to life visually.
Presentation Tools
- Microsoft PowerPoint
- Canva
- Google Slides
- Prezi
- SlideShare
- Beautiful.AI
Use presentation software to structure data narratives with flow, animations and visual punch.
Infographic makers
- Piktochart
- Venngage
- Infogram
- Canva
Infographics condense data stories into visually engaging, bite-sized graphics with charts.
Storytelling platforms
- JuxtaposeJS
- StorylineJS
- StoryMapJS
- TimelineJS
- Shorthand
Specialized storytelling platforms provide templates and functionality for crafting rich interactive narratives.
Photo/video
- Adobe Creative Cloud
- Canva
- Pixlr
- Animoto
- Powtoon
Images, video and animation can make data stories more visually compelling and accessible.
Written narratives
- Microsoft Word
- Google Docs
- Scrivener
- Hemingway Editor
Write and structure compelling long-form data stories using word processing programs.
What are some examples of great data storytelling?
For inspiration on crafting better data stories, here are some stellar examples to study:
Hans Rosling’s 200 Countries, 200 Years
This mesmerizing Gapminder animation brings global health and income data to life using motion and clearly-designed visuals. Rosling sets up a compelling mystery and reveals insights in a memorable narrative flow.
The Fallen of World War II
This interactive documentary uses innovative animations and stark visual design to illustrate the human cost of World War II. The emotional storytelling brings dry historical data painfully to life.
A Game of Shark and Minnow
The New York Times combined data visualization, illustration and rich multimedia storytelling to reveal the dynamic between China and its neighbors contesting islands in the South China Sea.
Snow Fall: The Avalanche at Tunnel Creek
This pioneering web-based story from the New York Times combined longform text, video, animation and parallax scrolling to recount a deadly avalanche disaster. The immersive experience blurred the lines between documentary and entertainment.
Weapons of Math Destruction
In her acclaimed book, Cathy O’Neil crafts data-driven narratives around chilling real-world cases of algorithms causing harm. By humanizing data, she makes the stakes powerfully clear for readers.
How can I start learning data storytelling?
Here are some ways to start building your data storytelling skills:
Consume examples
Immerse yourself in data stories from leading sources like The New York Times, Wall Street Journal, Quartz, fiveThirtyEight, ProPublica, and NPR Visuals Team. Study their narrative techniques.
Take a course
Take an online learning course focused on data visualization and storytelling, like those offered by University of Illinois, Telling Stories with Data and Knight Center for Journalism.
Experiment with tools
Get hands-on practice with data visualization, presentation and writing tools to find which ones suit your style and needs best.
Practice storytelling fundamentals
Hone fundamental narrative skills through reading, writing, and oral storytelling exercises. Learn from masters of fiction and non-fiction storytelling.
Analyze examples
Deconstruct examples of successful data stories. Analyze the use of narrative arc, visuals, language and other techniques that make them compelling.
Start small
Build your skills by creating simple data stories from scratch. Start with small personal datasets and straightforward tools.
Get audience feedback
Share your data stories with target audiences. Collect feedback on what resonates and what falls flat. Iterate to improve your storytelling.
Learn from experts
Read books, blogs and insights from leading data storytelling experts like Cole Nussbaumer Knaflic, Stephanie Evergreen, and Brent Dykes.
Expand your toolkit
Progressively learn more advanced data visualization, multimedia tools and programming languages like Python, R and D3.js to broaden your technical skills.
What careers benefit from data storytelling skills?
Data storytelling is a versatile skillset valued across many fields including:
- Journalism
- Digital marketing
- Business consulting
- Academic research
- Non-profit advocacy
- Design and product management
- Politics and public policy
Jobs where data storytelling skills are especially applicable include:
- Data journalist
- Data analyst
- Business intelligence analyst
- Marketing analyst
- UX designer
- Data scientist
- Digital marketing manager
- Market research analyst
- Content strategist
- Data engineer
Any role that involves gathering data, deriving insights, and presenting information to others can benefit from competency in data-driven storytelling.
| Career | Data Storytelling Application |
|---|---|
| Journalist | Researching data-driven news stories and presenting insights through compelling written, visual and multimedia narratives. |
| Data Analyst | Transforming analytic findings into engaging dashboards, reports and presentations for diverse audiences including leadership. |
| Marketing Manager | Crafting data-backed narratives and content to connect with target audiences and influence behavior. |
| UX Designer | Using data-driven personas, user journeys and narratives to bring clarity and empathy to the design process. |
| Consultant | Advising clients on strategic decisions by synthesizing data into compelling perspectives through reports, briefings and visual aids. |
| Researcher | Transforming complex findings from statistical analyses into clear written narratives and conference presentations. |
How can I improve at data storytelling over time?
Data storytelling is an evolving skillset. Here are tips for improving over time:
- Read across disciplines – Learn from great storytellers in journalism, film, literature, design and other fields.
- Get feedback – Ask readers, viewers and listeners what resonated or felt disconnected.
- Study the masters – Deconstruct stories from experts like Hans Rosling, David McCandless and Alberto Cairo.
- Join workshops – Attend sessions at conferences and meetups to exchange ideas.
- Observe response – Pay attention to body language and cues when sharing data stories live.
- Vary your stories – Experiment with new narratives, visuals, metaphors and medium formats.
- Practice regularly – Make time to exercise data storytelling skills, not just theory.
- Simplify ruthlessly – Remove elements that clutter or detract to keep refining your stories.
- Collaborate – Brainstorm ideas and co-create stories with complementary skillsets.
- Stay updated – Follow latest trends and tools in data visualization and narrative formats.
With a lifelong learning mindset, constant practice and openness to feedback, your data storytelling skills can continue to evolve and improve.
Conclusion
Data storytelling brings together the best of analytical and creative skills to produce truly compelling narratives. By learning key storytelling principles, experimenting with latest tools and actively honing your craft, you can become a skilled practitioner of this “data humanism” that enlightens audiences and spurs informed action. Whether your aim is to craft hard-hitting data journalism, inspire change through advocacy or lead organizations with data-driven insights, developing competency in data storytelling will give you an impactful edge in reaching people in today’s data-saturated world.