Power BI is standardizing on open-data formats by adopting Delta Lake and Parquet to help you avoid vendor lock-in and reduce data duplication. This minimizes data silos and fragmentation, offering a single source of truth across the enterprise. Direct Lake accelerates time to data-driven decisions by unlocking incredible performance directly against OneLake, without the need to manage costly, time-consuming data refreshes for large volumes of data in OneLake.
We recently made a significant update to the Direct Lake documentation, which goes into detail on topics including the following.
- The value of Direct Lake and in what scenarios. For example, semantic models on large volumes of data in OneLake vs. those created by a self-service analyst who needs agility to act without a dependency on IT.
- When Direct Lake should, and should not, be used instead of Import and DirectQuery modes.
- How Direct Lake works with Delta Lake data stored in OneLake. When and how the data is loaded, prepared and stored.
- How to secure, manage and monitor Direct Lake semantic models.
We intend to keep this documentation up to date as we continue to enhance Direct Lake in the future, so watch this space!
