Federate, mirror, or ingest: the decision between Databricks and Fabric

Federating, mirroring, and ingesting are not synonyms — and in Fabric "mirroring" already means three different mechanisms. When to use Lakehouse Federation, when to mirror a catalog or a database into Microsoft Fabric, when to ingest with Lakeflow Connect, what is actually free, and why source permissions do not cross the OneLake boundary.

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AI FinOps beyond caching: how to choose Batch, Model Router, PTU, and pay-as-you-go

Prompt caching solves reuse, but it does not decide when to run, how to buy capacity, or which model should answer. A practical framework for combining Batch, PTU, pay-as-you-go, and Model Router around cost per approved task.

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Data ontology: the governed context that makes AI reason across Databricks and Fabric

The bottleneck of enterprise AI is not the model, it is governed business context. How Unity Catalog Metric Views, Genie Ontology and Fabric IQ form a single semantic layer over one copy of the data — with an FSI use case, cost model and roadmap.

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