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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 13–17 of 17 posts
Compare star schema and snowflake schema designs for data warehouses with practical examples and guidance on when to use each pattern.
Establish consistent database naming conventions for tables, columns, indexes, and constraints that improve maintainability and team productivity.
Normalization is foundational to relational design but taken too far, it quietly sabotages analytics. This post explains why over-normalized data models break reporting performance, frustrate analysts, and create unnecessary complexity in modern data platforms.
Schema drift doesn’t crash pipelines or throw errors—but it slowly destroys confidence in analytics. This article explains how schema drift happens, why it’s so dangerous, and how enterprises can prevent it before trust is lost.
Poor naming standards don’t just create ugly schemas. They silently erode trust, inflate costs, and break analytics at scale. This article explains why naming is one of the most underestimated failure points in enterprise data warehouses.
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