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This project focuses on analyzing diabetes-related trends and predicting patient readmission risks through the use of ETL processes, machine learning, and interactive visualizations. A data pipeline was developed to integrate diverse datasets, allowing for detailed analysis and uncovering actionable insights for healthcare interventions.