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Microsoft Fabric and Power BI: capacity, refresh, gateways, semantic models and migrations. 12 posts.
Data written to a Fabric Lakehouse appears in Spark but not in the SQL analytics endpoint, or appears late. Understand the metadata sync, find tables it skipped and trigger a refresh as part of the pipeline.
When "revenue" means three things in three dashboards, trust in data drops. Decide where metric definitions live (BI semantic models, a headless semantic layer or platform metric views), how many BI tools to support, and how certified datasets, ownership and change control keep numbers consistent.
Slow Power BI reports usually come from a model that's too big or badly shaped, not from capacity. Measure with Performance Analyzer and VertiPaq Analyzer, move to a star schema, cut columns and cardinality, fix relationships, rewrite the slowest DAX, and use aggregations or Direct Lake where they fit.
Long full refreshes strain sources, gateways and capacities. Make Power Query fold to the source, configure incremental refresh with the right partitions, tune refresh parallelism with the enhanced refresh API, size gateways, and spread schedules away from peaks.
Fabric capacity sizing is about understanding capacity units (CU) over time, not peak minutes. Read the Capacity Metrics app correctly, find the items and operations that consume most, optimise them, separate workloads across capacities, set surge protection, pause non-production capacities and only then choose the SKU and commitment.
Plan the move from a Synapse dedicated SQL pool to a Fabric Warehouse. Check T-SQL surface differences, use the Fabric migration assistant, move data through OneLake, re-point pipelines and Power BI, and size Fabric capacity.
Move workspaces from Power BI Premium per capacity to Fabric F SKUs. Map P to F sizes, create the Fabric capacity in Azure, reassign workspaces with no content changes, check region and features, and manage cost with pause and reservations.
Move SSAS Tabular or Azure Analysis Services models to Power BI semantic models on Premium/Fabric capacity. Check compatibility, deploy through the XMLA endpoint, rebind data sources and security, redirect reports and retire the servers.
Build a gateway cluster for Power BI and Fabric so refreshes and DirectQuery survive a gateway machine failure, with load balancing, consistent drivers, recovery keys and a safe update routine.
Understand Fabric's smoothing, overage and throttling stages, find the items burning capacity units in the Capacity Metrics app, and fix it by tuning, rescheduling or scaling.
Plan Fabric capacities per environment or workload, structure workspaces and domains, lock down tenant settings, and use Git integration with deployment pipelines for dev, test and prod.
Read the refresh history error, then fix gateway connectivity, expired credentials, mismatched data source definitions, timeouts and capacity limits.
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