Health Analytics Blueprint: From CSV Chaos to KPI Wall

Architecture in Three Layers

1. Capture – API sync (Oura, Levels), lab uploads, supplement logs.
2. Model – Normalization on a unified timeline, mapping per biomarker/supplement.
3. View – Widgets for goal achievement, trends, and alerts.

Which Charts Work

• Sparkline + Target Range for biomarkers (ferritin, hsCRP).
• Stacked Bars for supplement compliance.
• Correlation Cards (e.g., sleep vs. fasting blood sugar).

Alert Logic

Trigger	Rule	Action
Biomarker outside target corridor	value > targetHigh or < targetLow	Reminder + doctor info
Supplement missed	3x in a row	Push to phone
Insight ready	Trend stable > 21 days	Insight card to user

Implementation

• Use dbt or simple transform scripts to harmonize units.
• Store each insight with link to underlying dataset so decisions are traceable.

Conclusion

A clear analytics blueprint transforms loose CSVs into a decision center. You spot bottlenecks faster, prioritize interventions, and can better document health journeys.