You're a data visualization professional. How can you make your designs more compelling? (2024)

Utilize storytelling techniques to contextualize data and make it relatable. Strive for simplicity and clarity while maintaining visual appeal to captivate and resonate with your audience.

Before choosing a visualization format, it's essential to understand the nature of your data and the story you want to convey. Consider whether your data is categorical, numerical, or time-series, and identify the key insights or trends you want to highlight. Choose the rights visualization type considering the audience and what you want to convey to them and what they can understand, with clarity and effectiveness. And iterate and test your data visualizations and designs and get feedback.

Clutter also starts with knowing who you visualize for. Knowing your audience also makes sure you know the level of clutter they can handle. Not everything can be seen as clutter as sometimes information is really needed to get the story out of your data. Data visualization is often seen as making complex data simple, but in the essence it's about making complex data understandable, and that's a significant difference.

To simplify and declutter data visualizations:1. Focus on key insights, removing unnecessary data.2. Limit data points/categories to prevent overcrowding.3. Use clear labels and titles for easy understanding.4. Minimize decorative elements to reduce visual noise.5. Utilize white space to separate elements and improve readability.6. Group similar data to highlight patterns.7. Provide interactive options for exploration.8. Seek feedback to refine and improve the visualization's clarity and effectiveness.

Context is key to data visualisation. As the creator of a visualisation, it is easy to provide too little context as you have been working on it so closely.Try to view your visualisation with fresh eyes, or ask someone else to look at it.Are your titles clear and relevant? Do you have legends? Are outliers annotated? Do you have a footnote showing information about your data?Without context your visualisation can be confusing to the casual viewer. And a confusing visualisation cannot be compelling.

Avoid questions in the format of, “do you like my design?”, otherwise you will get uninspiring false positive affirmations. Instead, probe for feedback on specific elements.

Design is about being inspired as well.I now use AI to spark this initial inspiration. I use midjourney for instance to generate a start for my dashboards, to get a glimpse of what it could look like.Of course, you can’t copy paste those designs into a real design tool like photoshop, figma, or even powerpoint, but it gives you a start and you can use certain elements of it.I now even paste chatGPT answers into midjourney to make the maximum use of AI to spark the inspiration. Next to that, I also go to sites like dribbble or pinterest to get inspired.

To make data visualizations more compelling, focus on:- Clarity: Ensure the message is clear and easy to understand.- Engagement: Use visually appealing elements to capture attention.- Interactivity: Allow users to explore and interact with the data.- Storytelling: Present data in a narrative format to engage emotions.- Context: Provide relevant context to aid interpretation.- Simplicity: Avoid clutter and complexity, prioritize simplicity.- Consistency: Maintain a consistent style and format across visualizations.- Accessibility: Make visualizations accessible to all users.- Feedback: Gather feedback to continually improve designs.- Innovation: Experiment with new techniques and tools to push boundaries.