The core principle established is that time intelligence functions in data modeling engines operate by automatically removing existing filters from date columns to ensure calculation consistency across all visible dates within the defined period, rather than respecting slicers or other filter context as default behavior. This mechanism relies on formal definitions involving "date tables," "filter contexts," and implicit `ALL` operations applied when a relationship connects to a marked datetime column. The concept belongs to the domain of analytical data processing and specifically addresses the interaction between scalar aggregations over time intervals and active visual filters, highlighting that standard time functions prioritize interval integrity over local filter constraints unless explicitly reconstructed.
The core principle established is that time intelligence functions in data modeling engines operate by automatically removing existing filters from date columns to ensure calculation consistency acro…