Apple Watch biometrics flowing through a production-grade data system. Idempotent ingestion, raw/clean/derived separation, anomaly detection, and full pipeline observability — built end to end.
⌚
Watch
→
📤
Export
→
🔄
Ingest
→
✅
Validate
→
🧮
Derive
→
📱
Dashboard
16
Health Metrics
3
Data Layers
19
Validation Checks
24/7
Apple Watch Sync
0
UI Metric Logic
🔄
Idempotent Ingestion
Date as primary key. POST the same day 100 times — always produces one clean record. Safe for retries, backfills, and re-exports.
upsertdate keyno duplicates
🗂️
Raw / Clean / Derived
Three immutable data layers. Raw is untouched. Clean is normalized and validated. Derived is computed-only. Frontend reads only from derived.
separationimmutable rawread-only UI
✅
Non-Destructive Validation
19 field-level range checks across all biometrics. Out-of-range values flagged with quality_flags[] — never rejected. Data always preserved.
quality flagsnever rejectclinical ranges
⚡
Pipeline Observability
Every stage monitored. SLA freshness per data source, event audit trail, anomaly detection across 6 biometric signals, live status indicators.
SLA trackingevent loganomalies
🧮
Metric Explainability
Momentum score (weighted 5-metric, 7-day rolling) and recovery readiness (rule-based: sleep + HRV trend + HR trend) with full contribution breakdowns.
weighted scoringlineageexplainable
🔬
Schema Inspector
Toggle between raw, clean, and derived layers live. See every field, type, value, and quality flag. Data lineage traces each metric step by step.
raw→clean→derivedlive schema
Built with
${['Apple HealthKit','Node.js + Express','Heroku','GitHub API','Vanilla JS','Service Worker (PWA)'].map(t=>`${t}`).join('·')}
🔒 Owner Access — Pawan Yandapalli
Full Access
Unlocks routine tracking, mood logging, and the full data inspector
Visitors can view Pipeline, Dashboard & About without signing in.
Once deployed, paste your Heroku URL here to enable live Apple Watch sync.
📱 Install Health OS — add to your home screen for instant access
TODAY
Maintenance▾
Grace
🎯
Today's Focus
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💡
Health Intelligence
Analyzing your health data...
Recovery
—
Momentum
—
Streak
0
→ days
7-Day Avg
0%
→ vs prior week
Today
0%
0 / 0 tasks
Mood Today
Energy Today
⌚ Apple Watch
Connect Health OS Backend
Enter your Heroku backend URL below to sync live Apple Watch data automatically.
Deploy the backend first, then paste your Heroku URL here.
👟
Steps
—
goal: 10k
📏
Distance
—
km walked
🪜
Flights
—
climbed
🧍
Stand Hours
—
goal: 12h
🏋️
Workout
—
goal: 30min
🔥
Calories
—
active energy
⚖️
Weight
—
Apple Health
📊
Body Fat
—
% body fat
❤️
Heart Rate
—
resting avg
💜
HRV
—
ms variability
🩵
Blood O₂
—
SpO2
🌬️
Resp Rate
—
breaths/min
🩺
Blood Pressure
—
mmHg
😴
Sleep
—
goal: 7–9h
🧘
Mindful
—
minutes
🫁
VO₂ Max
—
fitness level
ready
Health Overview
Last 7 days · public view
🔒 Sign in to see personal routine, mood tracking, completion heatmap & full analytics
Recovery Score · Last 7 Days
HRV Trend · 7 Days
Sleep · 7 Days
Health Intelligence
Last 30 days
30-Day Momentum
30 days ago
Today
Category Breakdown
Mood & Energy (7 days)
MOOD
ENERGY
Most Missed → Fix
Trend Signals
Weight Trend (from Apple Health)
No weight data yet — connect Apple Watch to auto-sync.
Completion Heatmap
LessMore
Personal Records
Correlation Engine
Patterns discovered from your data. Updates as you log more days.
⚡ Data Pipeline
Live view of the health data flow — Apple Watch → Backend → Dashboard
SLA / Freshness Monitor
Each data source has a freshness SLA. Green = within SLA, yellow = degraded, red = breached.
Anomaly Detection
Statistical flags on unusual readings vs your 14-day baseline.
Event Log last 20 events
🔬 Data Inspector
Raw → Clean → Derived pipeline transparency
Schema Inspector
Raw data — exactly as received from Health Auto Export, no mutation
Data Lineage
Select a metric to trace how it was computed, step by step.
API Reference read-only
Health OS
A personal health data system built as a data engineering portfolio project. Every design decision prioritises data correctness, observability, and pipeline transparency.
Architecture
Data Engineering Principles Applied
Tech Stack
Health Consistency Heatmap
GitHub-style contribution graph — each cell = one day of health data.