Disaggregated Data Demonstration

Disaggregated data has been broken down by detailed sub-categories, for example, by marginalized group, gender, region, or level of education. Disaggregated data can reveal deprivations and inequalities that may not be fully reflected in aggregated data. Because of intersectionality, disaggregated data is essential to understanding student success.

Analysis of disaggregated program data (in this demo, we are looking at Career and Technical Education programs) over multiple years is a critical first step in understanding the experiences of our students so that we can take action to close gaps and improve equity and access for every student. If you are funded through the federal Carl D. Perkins Career and Technical Education Act, this level of examination and reporting of efforts is a requirement.

Want to learn more? Contact us for training to build your data dashboards or support your team in data-driven professional development.