Machine Learning Feature Engineering for Student Retention

Develop a sophisticated SQL transformation pipeline in MySQL that prepares student demographic, academic, and engagement data for machine learning student retention prediction models. Create stored procedures that perform feature engineering including: z-score normalization, categorical encoding, interaction feature generation, and automated outlier detection. The solution must handle mixed data types and support scalable feature generation for datasets with 100,000+ student records.