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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.
Showing 13–18 of 81 posts
The complete data model for pharmacy claims, prescription management, and PBM data — including NDC normalization, DEA number validation, and dispensing fact table design for Snowflake and Databricks.
Pharmaceutical companies run the most complex data pipelines in any industry. Here is a complete 2026 competitive landscape comparing Snowflake, Databricks, BigQuery, Azure Synapse, and SAS for pharma-specific workloads: clinical trials, pharmacovigilance, real-world evidence, and commercial analytics.
Healthcare ETL has two very different schools of thought: Informatica, the enterprise incumbent used by health plans for 20+ years, and dbt, the modern SQL-first transformation tool taking healthcare data teams by storm. This guide breaks down exactly when each one wins.
Google BigQuery and Amazon Redshift are the two most widely used cloud data warehouses for healthcare claims analytics outside of Snowflake. This guide compares both platforms across HIPAA compliance, HEDIS reporting, FHIR integration, DDL syntax, and cost at scale.
Healthcare data teams face a critical architecture decision in 2026 — Snowflake's proven SQL warehouse or Databricks' open lakehouse. This guide compares both platforms across claims analytics, FHIR ingestion, HEDIS reporting, clinical ML, and cost at scale.
Every healthcare data warehouse eventually fails a HIPAA audit, produces a wrong HCC score, or generates a failed HEDIS submission — and traces the problem back to a missing or inconsistent data dictionary. Here is how to build one that actually gets used.
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