Now that you have your data, it's time to take a hard look at it:

What patterns of inequity immediately “jump out”?
What student groups appear to experience the most significant disparities?
Are there areas in which disparities appear to cluster?
What do the data tell us about how the institution is serving minoritized students?
- NOTE: Some will be tempted to focus on the students (maybe they aren't prepared, maybe they are working too many hours, maybe they have families at home, etc.); try to put those aside and ask yourself "regardless of why our student might be struggling, what do these outcomes tell us about how we are serving them?"
What are some tentative conclusions (or hunches) that might explain the disparities? (see same note above)
What additional data do we need to examine to better understand these disparities?
Are there some “non-traditional” data sources we should consider examining?
What else do we need to know?