Why should I ‘refresh’ Direct Lake models in Microsoft Fabric?
Published on:
Learn moreRelated posts
Understand Power BI Semantic Model Size | Memory Error Fixes (Part 1)
If you've ever encountered the "We cannot complete the requested operation because there isn't enough memory" error in Power BI, then this art...
How to determine if Direct Lake dataset is falling back to Direct Query in Microsoft Fabric
If you are looking to better understand the behavior of Direct Query and Direct Lake datasets in Microsoft Fabric, this tutorial will guide yo...
Improvements for creating new Direct Lake semantic models
As part of our continued tooling improvements, we have enhanced the experience for creating Direct Lake semantic models in Microsoft Fabric. T...
Model explorer with calculation group authoring is now available in Power BI service including Direct Lake semantic models
With the model explorer available for editing data models in the Power BI service these semantic models, both Direct Lake and those in import ...
What Does It Mean To Refresh A Direct Lake Power BI Dataset In Fabric?
If you’ve heard about the new Direct Lake mode for Power BI datasets in Fabric you’ll know that it gives you the query performance...
Understanding data temperature with Direct Lake in Fabric
As part of Microsoft Fabric, a new storage mode to connect from Power BI to data in OneLake has been introduced. Direct Lake it makes to possi...
Performance Testing Power BI Direct Lake Mode Datasets In Fabric
How to run performance tests on Power BI Direct Lake datasets in Microsoft Fabric
Performance Testing Power BI Direct Lake Mode Datasets In Fabric
How to run performance tests on Power BI Direct Lake datasets in Microsoft Fabric The post Performance Testing Power BI Direct Lake Mode Datas...
40 Days of Fabric: Day 4 – Direct Lake
Day 4 of the 40 Days of Fabric series explores Direct Lake and its benefits over traditional DirectQuery or Import storage modes in Microsoft ...