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databricks Platform · Updated Jan 19, 2026

Level of detail expressions for custom calculations

Level of detail expressions let you control aggregation granularity independently of the dimensions in your visualizations.

What it does

Level of detail expressions let you control aggregation granularity independently of the dimensions in your visualizations. Use fixed level of detail expressions to aggregate over specific dimensions regardless of visualization groupings, or use coarser level of detail expressions to aggregate at a higher level by excluding dimensions. Common use cases include calculating percentages of total, comparing values to dataset wide aggregates, and creating cohort level metrics.

Why it matters

Reduces operational overhead and unlocks new capabilities for data teams on Databricks.

Recommended use cases
creating cohort level metrics.
Architecture
Databricks Platform → Platform
In short

Level of detail expressions let you control aggregation granularity independently of the dimensions in your visualizations. Use fixed level of detail expressions to aggregate over specific dimensions regardless of visualization groupings, or use coarser…

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Key takeaway
Level of detail expressions let you control aggregation granularity independently of the dimensions in your visualizations.
2026-01-19-level-of-detail-expressions-for-custom-calculations Generated by the Databricks Updates Agent · browse all updates