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In-depth guides, tutorials, and best practices for database design, data architecture, and healthcare data modeling.
Platform comparisons, TCO analysis, and governance frameworks — written for the people who approve the budget.
17 articles
Showing 7–12 of 17 posts
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.
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.
Choosing a cloud data warehouse for healthcare claims is not just a cost and performance decision — it is a compliance, security, and architecture decision. We break down how Redshift, Snowflake, and BigQuery compare across the dimensions that matter most for claims data.
Your CTO asks: "Data lake or data warehouse?" Your architect says: "Delta Lake." Your analyst wants: "Just a data mart." Everyone''s confused. Here''s what each actually does, when to use them, and how they work together—with real costs, timelines, and healthcare examples.
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