Each exported table has its own filtering flow, which depends on the activity of various GLOBAL and LOCAL filters. The influence of individual filters on the table export as a whole can be described by the following logical pattern:
Filters for the main entities of the exported table, mainly concatenating. That is, they increase the amount of data in the result set as the number of selected items increases.
Filters for dependent entities - mainly filter data. They filter out the values collected by the main entity filters.
As an example, consider the Sprint Report Issues table.
For this table, the main entity is the board.
The sprint is associated with the board and is a dependent entity.
The issue is associated with the sprint and is also a dependent entity.
Thus, if we activate filters by projects and boards, the filtering results are concatenated.
If after that we add other filters related to sprints. We will get a result set with less data.
If we activate filters by issues, the resulting data set will also be reduced.
Thus, each of the exported tables has its own filtering flow, which can be used to achieve maximum filtering flexibility.