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This canvas is a comprehensive delivery performance analytics and predictive modeling workflow that analyzes Olist e-commerce order data to identify factors driving late deliveries and their impact on customer satisfaction. The workflow flows sequentially from exploratory data analysis through multiple dimensional analyses (geographic, temporal, product-category) to a Gradient Boosting classification model with feature importance analysis, producing actionable insights across 96,478 delivered orders with recommendations for supply chain optimization.