When you create a Direct Lake semantic model, it typically operates in Direct Lake mode. This means it directly accesses the delta table from the OneLake. This is the preferred scenario because it helps queries run fast, sometimes as fast as import mode. In Power BI, when utilizing Direct Lake mode, the semantic models directly […]
Author: Adrian Chodkowski
Why should I ‘refresh’ Direct Lake models in Microsoft Fabric?
You’ve probably heard about a new mode for datasets/semantic models called Direct Lake. This mode combines the advantages of existing modes: the performance of Import mode and the lack of need to refresh or cache data from Direct Query. It works by directly accessing files from a one lake without requiring extra steps. This means […]
Notebook orchestration in Microsoft Fabric made easy
When I meet with customers, we discuss how to efficiently organize notebook execution via orchestration mechanism. They often mention managing it manually using tools like Azure Data Factory. On the other hand, they sometimes express that Data Factory is too simplistic and they require other tools to address their needs. Similar questions arise regarding Microsoft […]
Retrieve execution query history in Databricks
Collecting the history of query and command executions in Azure Databricks is essential for troubleshooting, optimizing performance, and ensuring robust security measures. This practice establishes an audit trail for swift issue resolution, aids in creating a usage baseline for objects, and contributes to maintaining a secure data processing environment. The historical data becomes a valuable […]