Considerations for Ensuring Data Aggregation Is as Inclusive as Possible

Jonathan Schwabish & Alice Feng, Urban Institute

Data analysts sometimes lump together populations with small sample sizes—often racial and ethnic groups—out of convenience. But doing so can have harmful effects on those communities.

Combining groups with different experiences can obscure specific communities’ circumstances and paint an inaccurate picture. This prevents people from seeing their lives and experiences reflected in the data, can lead to misleading analyses, and can prevent decisionmakers from making policies that can create better outcomes for those communities.