After migrating to GCP, the organization had cloud infrastructure but no data strategy. Teams were spinning up ad-hoc queries and one-off exports. There was no consistent way to measure clinical outcomes, and AI vendor evaluations kept stalling because no one could provide clean training data.
Implemented a structured data platform layer on top of existing GCP infrastructure. Consolidated EHR extracts, claims data, and patient-reported outcomes into a governed warehouse with role-based access. Built reusable transformation pipelines and a catalog so both analysts and future AI workloads could discover and trust available datasets.
Enabled the first organization-wide clinical outcomes dashboard within 6 weeks. More importantly, created an AI-ready data foundation that allowed the team to move forward with an NLP vendor evaluation using real, validated patient data.
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