I went to the Tableau Conference— Here’s what I learned— Part 2

By: Anna Cave
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Data inclusivity edition.

This past week, Tableau hosted its annual conference completely online to make it accessible and free to anyone with a Tableau account. The conference took place over 3 days with 30-minute sessions on a variety of topics related to data.

The conference was incredibly eye-opening, and if you didn’t have a chance to catch it, the recorded sessions are still available on Tableau’s website. During the conference, I attended a few sessions on inclusivity and data ethics. 

The session hosted by Mark Nelson and Sarah Rosen Wartell, titled Data, Ethics, and Leadership in 2021, focused on the importance of using ethics before data is even collected. When used as a tool, data is incredibly persuasive in getting people to make decisions. Though data isn’t the only factor people take into account, it provides something more concrete for people to make decisions on, which often takes away some of the stress and instills confidence in the decision-maker. Unfortunately, data can’t work to that advantage if it isn’t collected ethically.

Data ethics need to be exercised in all parts of the process, from thinking about a set of principles needed to gather information to protecting that information after it is collected. Data reflects people in communities and oftentimes, particularly in marginalized communities, it is not collected or used fairly. There needs to be a balance between needing data and making sure you’re protecting the people you come from. 

Additionally, it’s important that data gets collected with limited biases. When you make decisions off of biased data, you are further enforcing those inequalities, so it is important to be careful throughout the entire process. It’s also important to look at the information in context and collect it in a way that allows you to disaggregate it so you can get as detailed as possible when needed. 

My favorite session of the whole conference was led by Emily Kund, titled Inclusive Design: Making Dashboards Engaging, Informative, and Accessible. Her presentation touched on how we can adjust our data visualizations to have more inclusive elements. Kund shared how to consider different types of exclusions people may have when it comes to visualizing data. Temporal exclusions can be situational, temporary, or permanent— something like holding a baby while trying to look at a visualization to having paralysis. Type exclusions have to do with sight (blindness, color blindness or limited vision), sound, comprehension and dexterity. 

Kund wanted to emphasize that we don’t all have the same experience and by designing with empathy for those different than us, we can create more accessible work. To successfully do so, Kund recommends learning and knowing who your audience is, understanding their challenges and recognizing any exclusions they may have before solving the problem and extending the solution to others.
 
Kund’s best tips for accessible visualizations are as follows:

• Consistency: keep consistent color usage; distinguish text appropriately as titles, headers, subheadings, and body copy so screenreaders can do their jobs; follow a consistent layout.
• Provide choice: make sure there is more than one way to do something so viewers can choose the best option for them.
• Prioritize content: remember to tell one story with your visualization. Draw attention to what is most important and pull out key metrics. 

These considerations are ones I wish I had in my back pocket long ago, but I am happy to be better informed now. For those interested in creating visualizations, I highly recommend watching Kund’s archived session, where she dives more deeply into how to dispel inequalities and inaccessibility to data. ​