Improving student performance for high-need student populations by improving the use of data in decision-making for early reading intervention programs in northwest Florida is the focus of this research to practice effort. The study is conceptually based on using a relational-feedback intervention (RFI) database model in early learning environments. The innovative use of data is the incorporation of trained classroom observers who performed over 2,000 observations (30 minutes each) in randomly selected reading (K–3) classrooms over a 2-year period using a quantitative observation tool that depicts 85 differentiated reading strategies. The RFI database model aligns classroom observation data to student achievement data with feedback interventions provided to schools. Empirical results that lend support for the use of the RFI database model include increased student achievement in early reading, closing of achievement gaps, increased informed decision making, and improved quality of professional development and communications about early learning for teachers/principals, stakeholders, and parents.