Data visualization is the art and science of presenting complex information in a clear and engaging way. It can help you communicate your message, reveal insights, and persuade your audience. But how do you simplify complex information with data visualization? Here are some tips to help you create effective and attractive graphics.
Before you start designing your data visualization, you need to know who you are creating it for. What is their level of knowledge, interest, and attention span? What are their goals, needs, and expectations? How will they access and interact with your graphic? Knowing your audience will help you choose the right format, style, tone, and level of detail for your data visualization.
Knowing your audience can mean knowing their expertise, comfort level, but also the themes they're familiar with. Are they spreadsheet-centric? Are they familiar with complex graphs or charts? If not, or you're unsure, it's best to use simple to understand themes, visuals, and ideas.
There are many types of charts and graphs you can use to display your data, but not all of them are suitable for every purpose. You need to choose the right chart type that matches your data and your message. For example, if you want to show trends over time, you can use a line chart or a bar chart. If you want to compare proportions or percentages, you can use a pie chart or a donut chart. If you want to show relationships or correlations, you can use a scatter plot or a bubble chart. You can also use more advanced or creative chart types, such as maps, heatmaps, histograms, or infographics, depending on your data and your goal.
When it comes to data visualization, one of the key principles is to simplify your design and remove any unnecessary or distracting elements. You should focus on the data and the message, not the decoration or embellishment. To achieve this, you should use a clear and consistent color scheme that reflects your brand and theme. Labels, legends, titles, and annotations can help explain your data and provide context. Additionally, fonts, sizes, and alignments should be easy to read and follow. Moreover, white space, grids, and borders can be used to organize and separate elements. Lastly, icons, images, and shapes can be included to add visual interest and meaning.
In my years of doing data-vis, I've learned less really can be more. Not all charts need legends or even metrics, if the bar chart or line does the talking for you. However, balance is key, and you want to make sure your designs are both visually beautiful but highly readable and understandable. A design that is sexy but hard to decipher - that's a fail.
Data visualization isn’t just about presenting numbers and facts, it’s also about forming a story. To capture the attention of your audience and guide them through your data and message, you can use storytelling techniques like setting the scene with background information, creating a narrative arc from beginning to end, highlighting the main points and key takeaways, using emotions, humor, or surprises to engage your audience, and asking questions or inviting feedback to encourage interaction.
The final step of data visualization is to test and refine your graphic. You want to make sure that your graphic is clear, accurate, and effective. To do this, you should check for errors, typos, or inconsistencies in both your data and design. Additionally, it can be beneficial to ask for feedback from colleagues, clients, or target audience. Lastly, you can measure the impact and results of your graphic such as views, shares, comments, or conversions. All in all, data visualization is a powerful way to simplify complex information and communicate your message. By following these tips, you can create graphics that are attractive, informative, and persuasive.