I think we’ve all been there… we are sharing a meaningful story we found in the data, only to have our end users get hung up on a previous peak or valley in our visualization. This often derails the conversation at hand and/or prevents our audience from hearing the rest of our message and/or reduces our chances of causing action.
One of the biggest challenges we face as data visualization practitioners is helping our end users avoid distraction. When our end users get distracted, it makes it more challenging to communicate the story in the data and our recommended actions. Ironically, one of the reasons users get distracted is because visualizing data makes it much easier to spot points of interest. Unfortunately, just because something may pique interest, it is not always relevant to the conversation.
This post shares an approach with the accompanying formula to do anomaly detection in Tableau. With anomaly detection, you’re able to focus in on the data points that matter and have a statistical explanation for your end users to help avoid distracting conversations.