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In-depth guides, tutorials, and best practices for database design, data architecture, and healthcare data modeling.
Showing 31–36 of 71 posts
The data lakehouse pattern — combining the scalability of a data lake with the ACID guarantees of a warehouse — is a natural fit for payer data. Here is how to build it on Delta Lake, layer by layer.
Not every healthcare claims use case requires real-time processing — and treating them all the same wastes resources and adds complexity. Here is the decision framework for choosing the right architecture.
Epic, Cerner, and Oracle Health are the three dominant EHR systems — and each requires a different integration strategy. Here is what actually works for extracting clinical data into your warehouse.
SDOH data is increasingly required for quality reporting, care management, and value-based contracts — but most warehouses treat it as an afterthought. Here is a practical data model that makes SDOH analytically useful.
Real-time clinical data demands event-driven architecture. ADT feeds, lab results, and prior auth events cannot wait for a nightly batch. Here is how to design Kafka-based pipelines for FHIR-native healthcare data.
Data mesh promises domain ownership and decentralized data products. But healthcare data — with its strict PHI governance, clinical terminology dependencies, and regulatory requirements — challenges every core data mesh principle. Here is an honest assessment.
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