How do you share data visualizations with others?

It is also helpful to keep Edward Tufte in mind and minimize your data-to-ink ratio. Extraneous detail, colors that don't convey a data feature, and other such frills, detract from your message. At the end of the day, your data needs to tell a story and it is up to you to frame your visualizations in a way that highlights the primary narrative arcs.

This depends on what your data visualisations are used for. In a presentation each visual should convey a clear message. In a dashboard it depends on the purpose of that dashboard. Is it a strategic dashboard that just delivers high-level metrics? Is it an operational dashboard that will be used frequently throughout the day? or is it an analytical dashboard that analysts will use to dig deeper into the data and spot patterns? Depending on which it is will depend on the level of detail your audience requires. Too often we develop dashboards with excessive detail resulting in key messages being lost. Less is often more in getting dashboard adoption and action taken off the back of it.

Understanding your audience's know-how about the topic and how well-versed they are with the technicality helps in choosing the appropriate level of language and terminology so that your narrative could be easily understood by the clients or audience. Another thing to keep in mind is the granularity of your data, and this is also depending on the prior knowledge of the audience and the depth of information they need. It doesn't matter how good the visualization or narrative is if the audience can't grasp your story. So the most important aspect is to keep your visualization in line with the needs and expertise of the audience.

Data granularity & how much flexibility you allow the target audience to interact with the data is also important. Too much flexibility & the intended focus & insights these are meant to convey will be lost with the "noise" caused by natural curiosity. It's important to start for each target audience a clear purpose to be served with a visualization, and avoid the temptation of adding more to it by default.

Are you presenting some analytical findings or building a dashboard for analysts to explore data? If you are sharing your findings then keeping it simple and making sure each visual leads to an outcome or action based on your analysis is key. If you are producing an analytical dashboard then more detail and options are required. There are very few occasions when animated gifs are required for presenting analysis. Keep it simple.

Not only this by selecting the right format for your data visualizations, you can improve the accessibility, promote interactivity, align with the medium and platform, cater to data complexity, facilitate storytelling, and ensure compatibility. These considerations contribute to effectively sharing your insights, engaging your audience, and enabling them to comprehend and interpret the data effectively.

To optimise your design consider exploring the Gestalt principals of design. Similarity, continuation, closure, proximity, figure/ground, and symmetry & order. These enable ease of understanding and allow for less ink on the page. This will reduce cognitive load on your audience. Test out your visuals with different people, can they easily tell you what they mean? In a dashboard, what draws people's eyes first and how do they visually navigate? Are they drawn to the least important metric first? Or maybe the pretty map you added because it looks cool?

Now before we go to the third step and deep dive into exploring the data visualization we need to ensure that the data is accurate, complete, and properly formatted. Cleanse the data, handle missing values, and perform any necessary transformations or aggregations. This step is essential for generating reliable and informative visualizations. As the most important thing to remember in data visualization is "Garbage in Garbage out".

Before we share data visualizations, we need to focus on the most important insights. Identify the key findings and communicate them clearly. Use titles, annotations, or callouts to highlight noteworthy trends, outliers, or correlations. Make sure the main takeaways are easy to understand and memorable for your audience.

When presenting your data, each slide should convey a clear outcome or takeaway. This context is what brings your visualisations to life. Instead of labelling your chart. Sales per year. Label it with a key takeaway, sales for 2023 are 5% higher than sales in 2022.

It is very rare that you will be sharing your data visualisations with large audiences. In the case that you are there are a few things to consider. Who should have access to this data? Most things you analyse in a company won't be in the public domain. Most things won't be shared across an entire company. Keep in mind data privacy. If you are able to share your data visualisations with a large audience then they are even further away from the context of your data. In this case your visualisations need to be kept incredibly simple to give the best change of comprehension. Check out the gun deaths in Florida chart for a clear example of where this goes wrong.

Offering multiple methods to use your data visualization can increase the prospect that others subsequently share it. Providing live URL links, embed codes, and image formats lets your target audience choose how they use your work. Although data visualizations alone are not known for yielding strong SEO results, never underestimate the potential for SEO to promote your data visualizations, especially in the future. You can optimize your titles, descriptions and tags with relevant keywords to make your visualization more discoverable in Search.

This should not be the last step. Produce some visuals and go and talk to them with your stakeholders. Can they interpret what you mean? Or do you have to explain the data to them multiple times? You can measure dashboard usage, but the rest of the suggestions in this post are nonsense for 99% of people. If someone sent a survey to me asking about their data visualisations there is no chance I would fill it in. People in the rest of your organisation have a day job to do, not to fill in surveys on an individual data visualisation that you produced for a company blog.