Do you actually need Microsoft Fabric, or is Power BI enough?
When Power BI is genuinely enough, when Microsoft Fabric is worth starting early, and what a capacity really costs. A practitioner’s decision framework.
Category: Delivery Patterns
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The Fabric architecture for financial institutions
Walk into almost any bank, credit union, or insurer and you find the same problem: every system reports its own totals and reconciling them burns days. Here is the Microsoft Fabric reference architecture that fixes it, and why the certified semantic model, not the plumbing, is the product.
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Beyond DP-600 and DP-700: The Quieter Fabric Training Catalog
Most data teams considering Microsoft Fabric training go straight to DP-600 or DP-700. There is a quieter catalog underneath it that fits most teams better: one-day courses (DP-601, DP-602) and Microsoft Applied Skills credentials. Here is when to pick which.
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Microsoft Fabric Naming Conventions: Five Rules That Hold Up in Production
Naming conventions are the thing every Fabric project starts with good intentions and abandons by month three. The fix is not better discipline. It is AI as a deterministic enforcement layer. Here is the standard I use on every project, in five rules.
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AI in Fabric Development: A Power Multiplier, Not a People Replacement
Most of what is written about AI in data work falls into two buckets: AI will replace developers within two years, or AI is glorified autocomplete. Both are wrong. After months of daily use on Microsoft Fabric engagements, the honest answer is that AI is not a people replacement but a power multiplier, and like…
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What Does Monitoring Your Fabric Capacity Actually Cost?
A reader asked the right question after our last post on three-layer pipeline monitoring: what does it cost in CUs? Microsoft has not published authoritative figures, and the Capacity Metrics App will not separate monitoring overhead from everything else your Eventhouse is doing. The only way to get a real number is to measure. Here…
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Three Layers of Pipeline Monitoring We Deploy on Every Fabric Engagement
Out of the box, Microsoft Fabric pipelines fail in ways that are easy to miss. After a couple of years shipping Fabric platforms into production, we now deploy the same three-layer monitoring pattern on every engagement: collect with Workspace Monitoring, diagnose with saved KQL queries, notify with tiered Data Activator triggers.