Applying sensitivity labels in Power BI has no or only negligible effects on report performance and load times during ordinary circumstances. Sensitivity labels are mainly assigned metadata to objects (such as reports or datasets) and, depending on configuration, can additionally add actions like marking content or encrypting content. These were meant to provide security and compliance, not conduct data processing, so they're likely not going to interfere with data rendering or query execution inside Power BI.
However, Performance factors might come into play if sensitivity labels are set up with encryption via Microsoft Purview. For example, encrypted material may incur extra validation or access token verifications, creating minimal delays when accessed for the first time—particularly in the presence of convoluted identity or conditional access policies. Likewise, when data is exported out of large sets, action-blocking labels can impose minor authentication latency or restrict optimization strategies.
In order to mitigate possible slowdowns:
- Only use encryption-based labels on high-traffic or performance-sensitive reports when necessary.
- Apply scoped labeling policies to label only sensitive datasets.
- Educate users about how label inheritance works to avoid over-labeling, which can lead to wider-than-necessary restrictions.
- Report usage through Microsoft 365 audit logs to monitor label-related access events and detect any bottlenecks.
