MSBI Tutor

Many enterprise Power BI semantic models use Azure Databricks as a data source. When building these models, developers and architects face an early and consequential decision: which storage mode to use. Cost, security, and ease of development and tuning all factor in — but report performance is probably the most important of them, because reports that are slow to load are one of the most common causes of end-user dissatisfaction. In practice, that decision is often made on intuition rather than evidence. To help change that, we've published a new white paper, Modern Power BI Architecture Choices for Reporting on Azure Databricks , benchmarking four ways of serving the same Delta tables to a Power BI report: Direct Lake on OneLake — over Delta tables in a Fabric lakehouse or warehouse Direct Lake on mirrored Unity Catalog tables — shortcuts, no copy DirectQuery — on a Databricks SQL warehouse Composite Model on Databricks — DirectQuery combined with Import-mode aggregations Figu...

With the general availability of the new Power BI defaults , we’ve refreshed many of the sample reports you already know. The updated samples pair cleaner, more consistent report design with stronger semantic models, giving you practical examples that are easier to explore, learn from, and reuse. Download the refreshed 2026 Power BI sample reports and open them in Power BI Desktop to see the changes for yourself. What’s new This refresh goes beyond visual polish. We improved both the semantic models and the report experience, so each sample demonstrates current best practices from data preparation through report consumption. Stronger semantic models A well-designed semantic model makes reports easier to build, understand, and maintain. Across the samples, we: Renamed tables, columns, and measures so their purpose is clear. Added concise descriptions to guide report authors. Created measures for common analysis, such as win percentage and high backorder risk. Applied consistent display...