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HealthTech Data Platform Modernization

Rebuilding a fragmented analytics stack into a governed, self-serve platform for clinical and operations teams.

Project: HealthTech Analytics Platform
Tech: Snowflake, dbt, Airflow, Looker
Completed: Placeholder — Month YYYY

The Results

Modernization unlocked faster insight delivery and better governance across clinical reporting.

Placeholder +XX%
Reduction in report turnaround time
Placeholder -XX%
Decrease in data quality incidents
Placeholder X
Departments onboarded to self-serve

Placeholder note: Metrics above are illustrative until final client approvals are confirmed.

The Challenge

Clinical teams relied on a patchwork of spreadsheets, manual SQL exports, and inconsistent metric definitions. Data refreshes were slow, audits were painful, and conflicting numbers undermined trust.

Core Pain Points

Single-source-of-truth issues, delayed reporting cycles, and limited access to governed datasets.

The Solution

We consolidated data into a centralized warehouse, standardized transformation logic, and introduced semantic models for consistent metrics across teams.

Platform Blueprint

Ingestion Modernization

Replaced ad-hoc extracts with scheduled pipelines and automated data validation checks.

Metric Governance

Defined shared metric definitions with clinical leads and embedded them in dbt models.

Self-Serve Analytics

Delivered curated data marts and Looker explores to reduce analyst bottlenecks.

Snowflake dbt Airflow Looker

Impact

Leadership gained reliable dashboards for operational planning while analysts reclaimed time previously spent on manual data prep.

Before

Weeks
Reporting cycle time

After

Days
Reporting cycle time

Key Takeaways

Governance Enables Speed

Shared metric definitions and automated tests reduced rework and built stakeholder confidence.

Self-Serve Scales Teams

Curated data marts and enablement sessions helped clinicians and operators answer questions independently.

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