Stabilizing CAFÉ in Production and Reframing INSIGHT Strategy

This week, I split my effort between production support for CAFÉ and core data strategy work for Insight.

For CAFÉ, I focused on production patches because active issues surfaced in live use. I applied targeted fixes to address errors quickly and keep the system stable for users. The goal was to reduce disruption, prevent repeat failures, and keep operations smooth while the platform is already in production.

For Insight, I explored a major direction change. I created a separate branch to redesign the schema and shift to PostgreSQL, since the project is heavily analytics-focused and I am working with row-based dataset uploads from Excel files submitted by HEIs. During this exploration, I found that row-level mapping was still too inaccurate and required too much manual intervention. Because of that, I decided not to force the new path yet. I kept the current structure and moved forward with a consolidated dataset upload approach, which is more practical and stable at this stage.

I also continued improving analytics workflows, including dashboard and table improvements, enrollment warning handling, and automatic warning-fix actions to reduce repetitive cleanup work.

Laravel, Antigravity, VS Code, XAMPP, Git, GiHub, Vue

A key challenge this week was balancing urgent production maintenance in CAFÉ with long-term architecture decisions in Insight. I addressed this by prioritizing production patches first, then allocating focused blocks for strategy and implementation work in Insight.

Another challenge was deciding whether to proceed with a full schema and database redesign. After testing the branch and reviewing mapping accuracy, I chose the safer and more reliable approach: keep the existing setup and use consolidated uploads while improving validation and warning automation.