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The recent addition of Excel Drill‑Through support for Direct Lake models is a welcome improvement. However, this change introduces a significant governance and usability challenge for large enterprise models.
In the current implementation:
Drill‑through is enabled by default for every measure
The default behavior exposes all columns from the underlying fact table
The only way to control this is to manually add a detailRowsDefinition to each measure
For large Direct Lake models with hundreds or thousands of measures, this is not scalable. We would prefer a governance model where drill‑through is disabled by default, and only specific, approved measures opt in.
To achieve controlled drill‑through today, we must:
Edit every measure
Add a “blocked” detailRowsDefinition for measures that should not allow drill‑through
Add a custom detailRowsDefinition for measures that should allow it
This is extremely time‑consuming and error‑prone at scale.
Additionally, the default Excel drill‑through behavior (showing all fact table columns) is rarely appropriate for governed semantic models and cannot currently be changed.
The only workaround is to:
Export the model as TMDL
Bulk‑edit all measures using scripts or AI
Re‑import the updated TMDL
This is not a sustainable long‑term approach.
A simple toggle in Power BI Desktop or the model properties pane that allows developers to invert the default behavior:
Off by default → Measures must explicitly opt in
On by default → Current behavior
This would immediately solve the governance issue for large models.
Allow model authors to specify a default drill‑through template or suppression rule, rather than relying on the fact‑table dump.
For example:
A model‑level drill‑through policy setting
A bulk‑apply option for detailRowsDefinition
A “block drill‑through” checkbox in the measure properties pane
These additions would make drill‑through governance far more manageable.
Direct Lake is designed for very large, enterprise‑scale models. These models often require strict governance, and the current drill‑through defaults create:
Data exposure risks
Inconsistent user experiences
Significant manual overhead
Providing model‑level control would align drill‑through behavior with enterprise needs and reduce unnecessary TMDL manipulation.
For reference, here’s the update announcement:
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