Automated Student Performance Trend Analysis Pipeline

Design a Laravel-based data pipeline that automatically aggregates student performance metrics from multiple source systems (Canvas LMS, internal grade databases, standardized test platforms). Create a modular ETL process using Laravel Horizon for background job processing that can: 1) Extract grade data from disparate sources, 2) Normalize and clean datasets, 3) Generate predictive learning trend reports, 4) Automatically email personalized insights to administrators and department heads. Include robust error handling, logging mechanisms, and support for incremental data updates with timestamp-based synchronization.