What is data disaggregation?
Disaggregation means breaking down large data categories into more specific subcategories. “Data disaggregation” refers to the collection, reporting, and analysis of information on specific subgroups by race, ethnicity, and other characteristics. When data are disaggregated, researchers are better able to analyze differences between groups, as well as the relationship between multiple variables, such as race and age.
Why do we need disaggregated data?
Aggregated data hide inequities. In many existing state and federal data collection systems, data are not sufficiently disaggregated by race and ethnicity (including subgroups and first language), sex (including sexual orientation and gender identity), disability, age, income, and other characteristics like geographic area or social determinants of health. This masks the nuanced realities of many communities behind larger trends, and makes it more difficult to address inequities. As just one example, aggregate data may perpetuate the model minority myth — that all Asian Americans have high levels of income, homeownership, education, and health — but disaggregated data reveal large disparities among AANHPI groups. For instance, the percentage of Asian Americans living below the poverty line ranges from 6.8 percent of Filipino Americans to 39.4 percent of Burmese Americans.
What are we doing about it?
The Education Fund and our partners in the Data Disaggregation Action Network are working to advance federal and state policies as they relate to data disaggregation by race and ethnicity. Through the creation of a state and national advocacy infrastructure to engage stakeholders and policymakers on the need for disaggregated data, we will ensure the collection, analysis, and reporting of critical federal- and state-level data that will help to identify gaps in and achieve racial equity.
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Data disaggregation resources
Research and reports:
- The Leadership Conference – Information Nation: The Need for Improved Civil Rights Data Collection
Data disaggregation blog series
- Data Disaggregation Deconstructed: AANHPI communities
- Data Inclusion is Vital for LGBTQI Equality
- Why the Census Matters for Disability Data Inclusion
- Civil Rights Data Collection Must Improve for Equity in Education
- Why the FCC Should Make its Employment Data Public
- Why Collecting Disaggregated Data for Native Communities Matters
- Why a MENA Category Matters