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Your Data Model Isn't Broken, Part II: The Refactoring Playbook

In [Part I], I made the case that your legacy data model isn’t the disaster it looks like. That the strange WHERE clauses, the bridge tables nobody can explain, and the slowly-changing-dimension-within-a-slowly-changing-dimension aren’t bugs — they’re business rules earned through years of production reality. I argued that big-bang rebuilds fail at alarming rates, that the complexity you’re fighting is mostly essential rather than accidental, and that the impulse to “start from scratch” is driven more by cognitive bias than by engineering judgment.

Saturday, March 28, 2026 Read
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That Tuesday Morning When I Finally Fixed Our Ten-Minute Queries

The Ten-Minute Query I’m sitting at my laptop on a Tuesday morning, waiting. The progress bar on my screen says ‘Query running… 4 minutes, 37 seconds.’ I lean back in my chair and let out this long sigh that probably says more than I intended. My manager walks past my desk. She glances at my screen, and I can see that look—the one that says she already knows what I’m about to tell her. I didn’t need to explain.

Friday, January 16, 2026 Read
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Streamlining Data Pipeline Reliability: The Write-Audit-Publish Pattern

Introduction: Why Safe Data Pipelines Matter In the world of data engineering, there’s a constant challenge we all face: how do we ensure our production data remains reliable and error-free when deploying updates? Anyone who’s experienced the cold sweat of a bad deployment affecting critical business data knows this pain all too well. Enter the Write-Audit-Publish pattern—a robust approach that can significantly reduce the risk of data pipeline failures. This pattern, which shares DNA with the well-known Blue-Green deployment strategy from software engineering, creates a safety net that can save your team countless hours of troubleshooting and emergency fixes.

Sunday, May 18, 2025 Read