Unlocking the Emotional Power of Data Visualisation and Storytelling
Reflections on my recent World Data Summit virtual roundtable about how data visualisation, storytelling, and AI come together to inform, inspire, and create meaningful impact.
Unlocking the Emotional Power of Data Visualisation and Storytelling
Reflections from the World Data Summit Virtual Roundtable
When I was invited to present at the World Data Summit’s virtual roundtable on data visualisation and storytelling, I saw it as an opportunity to reconnect with professionals from across the world who share the same challenge: how to make data meaningful. Around a hundred people showed interest through LinkedIn, and although the live attendance was smaller, the discussions were rich and genuine. Hosted by the amazing Anna Beklemisheva and the superb Alina Nizamtdinova, the event brought together returning faces and new voices in what is becoming a vibrant global network of data experts.
Understanding the Purpose of Data Visualisation
I opened the session by revisiting what data visualisation really is. For me, it sits at the intersection of data science, storytelling, and increasingly, artificial intelligence. It is both art and science, a layer of interpretation that allows us to see patterns that might otherwise remain hidden. Yet many professionals still struggle with visualisations that confuse more than they clarify. I shared an example of an over-complicated dashboard that failed to guide its users, not because the data was wrong, but because the story and design were never properly planned.
A Framework for Building Data Solutions
To tackle that, I introduced my four-step model for creating effective data visualisation and storytelling solutions. It starts with what I call Step 0: Contextualisation, a pre-production phase where you define the audience, clarify the problem, and decide the delivery format. This is the foundation of every good data story. In my book Sketch Your Data, I include a Context Definition Worksheet that helps professionals map this stage.
Once context is clear, Step 1 is to investigate the data and create evidence. Step 2 involves organising ideas into a narrative structure with a beginning, middle, and end. Finally, Step 3 is about delivering the message in a clear and memorable way.
Designing for the Audience
A major theme of my talk was audience-centric design. The way you present information to doctors, for example, should differ completely from how you present it to the general public. Even the reading gravity matters, especially in cultures where the eye naturally moves from right to left. I also encouraged participants to sketch their ideas before using software, as it helps build creativity and avoid over-reliance on tools.
I demonstrated Sketch Your Data, a visual reference guide app with built-in AI support, which helps users explore different chart types and storytelling techniques.
Managing Cognitive Load
Another key concept was cognitive load. Many visualisations, especially those built directly from standard tools like Microsoft Power BI, Tableau, PowerPoint, or even Excel, demand too much mental effort from their audience. Applying Gestalt principles helps reduce this strain by creating stronger figure–ground relationships and guiding the eye through hierarchy and proximity. The goal is to make complex information easier to digest through structure, grouping, and simplicity.
The Role of AI and the Future of Visualisation
I then explored how AI is reshaping the landscape of data visualisation and storytelling. Many tools are already integrating natural language generation to automate parts of the process. However, while AI can help with speed and consistency, it also introduces the risk of hallucination, especially when working with structured, tabular data.
Our role as data professionals is evolving from producing every element by hand to guiding AI systems with intent, creativity, and ethical awareness. I believe the future will require fine-tuned models and AI agents specifically trained for data visualisation tasks, where human oversight remains essential.
Storytelling and Ethics
Storytelling in data is not only about aesthetics but also about responsibility. Every chart and sentence carries an editorial stance. I discussed how tension, contrast, and analogy can make stories more memorable, and how repetition strengthens key messages. At the same time, accessibility should never be an afterthought. Choosing colour palettes that work for colour-blind viewers, selecting readable fonts, and writing in clear language are all part of ethical design.
Learning and Inspiration
To help participants continue their learning, I recommended several resources. Edward Tufte’s The Visual Display of Quantitative Information remains foundational. My own book, Sketch Your Data, combines planning tools with creative exercises. I also encouraged exploring adjacent fields such as statistics, UX design, and narrative theory. Even the hero’s journey framework, often used in literature and film, can guide how we build suspense and resolution in data storytelling.
Looking Ahead
The virtual roundtable series will continue later this year, and I look forward to joining future editions. The in-person World Data Summit in January 2026 in Kuala Lumpur will be another exciting opportunity to connect, share, and learn from one another. For those who attended the session, thank you for engaging and contributing your insights. For others who could not join, let us stay connected through LinkedIn and continue shaping how data stories are imagined and told.