Explore vs Explain

On day 2 of dashboard week we learned about effectively communicating through data viz. The two flavors of dashboards we should be building in our careers are Exploratory vs Explanatory.

Characteristics of an Exploratory Dashboard:
-discover:
--distribution
--variation
--shape
--size/magnitude

From phdata, "You are handing them a dashboard with the intent of having them dive in deep and find the answers on their own." From https://www.phdata.io/blog/dashboard-design-essentials-dashboard-layout-formatting/

When I think of building an exploratory dashboard, I think of providing as many filters and slice by options as possible to try and create as customizable of an experience as possible. I also think of exploratory dashboards as having more user interaction such as "enter your height and weight to find out what athlete you are most likely to be". More broadly, I expect exploratory dashboards to potentially have more complex chart choices such as a heat map or radar chart or violin chart that will make the user think harder and potentially uncover patterns or outliers that wouldn't have been as easily seen in a basic bar or line chart.

Characteristics of an Explanatory Dashboard:
-tell a story:
--what's going on?
--why is this happening?
-summative / current status
-check frequently

An explanatory dashboard's main purpose is to explain what has already happened. This typically means the data is already limited to just what is needed to answer a specific question or business requirement. Explanatory dashboards could often start with an over-arching question that gets specifically answered within the meat of the dashboard. A part of today's lesson that really stuck with me was "come up with headline or sentence to make someone go do something or look somewhere". This is what I believe should be the main motive when creating an explanatory dashboard; make someone notice it and then action on it.