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Large Scale Health Data Monitering With Databricks
A wearable healthcare company was generating massive high-frequency data in Azure Blob Storage, tracking metrics like heart rate, respiration, oxygen levels, and activity every minute.

Scope:
- Instantly alert users when heart rate crossed thresholds.
- Send personalized notifications and celebrate user milestones.
- Warn users of dangerously low oxygen levels.
Approach:
- Leveraged scheduled Databricks notebooks to process terabytes of incoming data and deliver near real-time alerts.
- Performed aggregated analytics (daily/weekly) and stored results in PostgreSQL for rapid access to frequently used metrics.
Outcome:
- 95% of abnormal readings detected in real-time.
- Significantly decreased query times for common metrics.
- Scalable solution capable of handling terabytes of high-frequency data.
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