Blog
Production-focused notes on Microsoft Fabric, data engineering, cost optimization, and data quality — the patterns I actually use, and the mistakes that taught me them.
Where Apps Really Break: Testing the UI–Backend Boundary
Most bugs don't live in the UI or the backend — they live in the seam between them. A beginner-friendly QA guide to finding the bugs other testers miss: slow networks, double-clicks, silent errors, and inputs the backend never checked.
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Use Claude AI Inside Microsoft Fabric — A Beginner's Step-by-Step Guide
Never called an AI API before? Walk through it click by click inside a Fabric notebook: get a key, store it in Key Vault, make your first call, then auto-label a whole table of customer comments with Claude.
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Build a Fabric Pipeline That Works in Any Workspace (Step by Step)
The most painful deployment mistake in Fabric — and the one small GlobalParam notebook that fixes it. Make a pipeline detect its own workspace so it runs correctly in dev and prod without changing a thing after deployment.
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How I Cut Our Microsoft Fabric CU Usage From 70% to 30%
Three real ways to reduce CU consumption in Microsoft Fabric: moving small workloads from PySpark to pure Python with delta-rs, switching full loads to incremental, and measuring what's actually burning your capacity — for ~$50K/yr less on the same SKU.
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More posts on the way. In the meantime, try my free data & QA tools or watch the tutorials on YouTube.