Methodology
From Raw Campus Data to Actionable Decisions
Our process is built for reliability at scale: schema-first, privacy aware, and optimized for real-time operations.
1. Data Normalization
Ingest room, course, schedule, student, and enrollment records into a normalized SQL schema with quality checks.
2. Spatial Intelligence Layer
Map room_raw values to building, floor, and zone context to support heatmap and occupancy calculations.
3. Prediction and Recommendations
Use historical traffic and live schedule sync to generate surge alerts, advisor suggestions, and campaign timing recommendations.
4. Operational Activation
Execute targeted push campaigns, export historical reports, and connect systems using the enterprise API access hub.