Power BI Embedded over Direct Lake

Power BI Embedded over Direct Lake mode semantic models is enabled, including full automation based on Fabric REST APIs. This allows ISVs to deploy and manage a solution, based on Direct Lake semantic models, to a very large number of their customer tenants. Direct Lake mode is a groundbreaking new engine capability to analyze very large datasets in Power BI. The technology is based on the idea of loading parquet-formatted files directly from a data lake, without having to query a Warehouse or SQL analytics endpoint, and without having to import or duplicate data into a Power BI semantic model. This native integration brings a unique mode of accessing the data from the Warehouse or SQL analytics endpoint, called Direct Lake.Direct Lake provides the most performant query and reporting experience. Direct Lake is a fast path to load the data from the data lake straight into the Power BI engine, ready for analysis.In traditional DirectQuery mode, the Power BI engine directly queries the data from the source for each query execution, and the query performance depends on the data retrieval speed. DirectQuery eliminates the need to copy data, ensuring that any changes in the source are immediately reflected in query results.In Import mode, the performance is better because the data is readily available in memory, without having to query the data from the source for each query execution. However, the Power BI engine must first copy the data into the memory, at data refresh time. Any changes to the underlying data source are picked up during the next data refresh.Direct Lake mode eliminates the Import requirement by loading the data files directly into memory. Because there's no explicit import process, it's possible to pick up any changes at the source as they occur. Direct Lake combines the advantages of DirectQuery and Import mode while avoiding their disadvantages. Direct Lake mode is the ideal choice for analyzing very large datasets and datasets with frequent updates at the source.