Concept
Semantic drift is the gradual divergence of business definitions such as metrics, measures and entity meanings across copied or forked data models, while names, schemas and security stay unchanged.
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2025-12-30 · Video on YouTube
Most organizations think their data problems are about who can see reports. In reality, the bigger risk is what those reports mean today—and how quietly that meaning changes tomorrow. Your transcript argues that Microsoft Fabric doesn’t create chaos by being…
2026-03-24 · Video on YouTube
This episode explains why data models in Microsoft Fabric naturally drift over time and why DAX cannot fix the problem. It argues that data models are not objective truth—they are human-made interpretations that embed assumptions, business logic, and…
2026-02-20 · Video on YouTube
In “The Context Advantage: Architecting the High-Performance Autonomous Enterprise,” the M365.FM podcast reframes where enterprise AI and autonomy succeed — not at the model or interface layer — but in the architected context substrate that underlies them.…
2026-01-22 · Video on YouTube
In this episode, Architectural Drift: Governing Autonomous AI Models in Power BI Fabric, we explore why modern analytics platforms like Microsoft Fabric and Power BI are not simply reporting tools, but are now part of a broader architectural ecosystem that…
Semantic drift occurs when the meaning of data metrics changes over time, often without oversight. It leads to discrepancies in reported metrics and undermines confidence in the data. · From the episode: Build a Trusted Semantic Layer in Microsoft…
No. The episode says Fabric excels at access control. It exposes a deeper problem that older architectures masked with friction: unmanaged semantic drift in how metrics and models are defined. · From the episode: Build a Trusted Semantic Layer in Microsoft…
Not because of bad models or poor prompts but because of context fragmentation: inconsistent identity, permissions, data silos and unmanaged semantic drift. These are the real bottleneck. · From the episode: Architect a High-Performance Autonomous…
Implement a strong semantic governance framework to keep definitions consistent, run regular audits and monitoring, establish clear ownership and accountability and integrate governance into the AI lifecycle. · From the episode: Govern Semantic and AI Model Drift in Power BI…
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Maintained by Mirko Peters (Microsoft MVP) · Last updated:
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