In this data science project, we partnered with a fictional government—Caladan—to design effective yet minimally restrictive COVID-19 policies using real-world international data. Our goal was to maintain the 30-day rolling average of new COVID-19 cases below 3% and deaths below 1%. We collected and transformed data from Azure SQL, Cosmos DB, and VM SQL Server into a centralized Operational Data Store using a Galaxy schema. Using tool Power BI, we visualized case trends and identified a “Golden Policy Zone,” where policy strictness balanced health outcomes with social and economic flexibility. Our solution provided actionable recommendations for school closings, gathering restrictions, and travel control based on statistical analysis and real-time data trends.