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Continuous Integration for Data Teams: Beyond the Buzzwords

The Day Everything Broke (And How CI Could Have Saved Us) Picture this: It’s 9 AM on a Monday, and your Slack is exploding. The executive dashboard is showing impossible numbers. Customer support is fielding complaints about incorrect billing amounts. The marketing team is questioning why their conversion metrics suddenly dropped to zero. You trace it back to a seemingly innocent change you merged Friday afternoon—a simple column rename that seemed harmless enough. But that “harmless” change cascaded through your entire data pipeline, breaking downstream models, dashboards, and automated reports.

Saturday, June 28, 2025 Read
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dbt Fusion: The Engine Upgrade That's Got Everyone Talking

When Your Favorite Tool Gets a Makeover You know that feeling when your favorite app suddenly changes its interface? That mix of excitement and anxiety about whether the changes will actually improve your workflow or just mess with muscle memory you’ve spent years building. That’s exactly what happened when dbt Labs dropped dbt Fusion on the analytics engineering community. The reactions were… let’s call them passionate. Some folks were celebrating like they’d just discovered fire, while others were questioning whether this marked the beginning of the end for open-source dbt.

Saturday, June 21, 2025 Read
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The Art and Science of Conceptual Data Modeling: Building Pipelines That Last

Introduction: Why Conceptual Data Modeling Makes or Breaks Your Pipeline Ever found yourself staring at a faulty data pipeline, wondering where it all went wrong? Join the club. I’ve been there too many times to count. The hard truth? Most pipeline failures aren’t technical issues—they’re conceptual ones. We get so caught up in the how (tools, languages, frameworks) that we completely miss the what and why of our data needs.

Saturday, May 17, 2025 Read