Reporting on Activity and Frequency: Its primary use is as a dimension in time-series charts to track development throughput. A column chart with a dimension like YEAR_MONTH(created_at) and a COUNT() metric creates a classic "Commit Frequency" report, showing the volume of commits over time. A commit has no branch of its own: to count the commits that went into a given branch, filter on the branch its pull request targets, such as Pull Request > Base ref > Branch = "main".

Analyzing Work Patterns: You can perform more granular analysis on your team's work habits. By using custom formulas, you can group commits by the day of the week with a dimension like DAY_OF_WEEK(created_at) or by the hour of the day with HOUR(created_at) to identify patterns, such as work happening over weekends or consistently late at night.

Filtering by Time: As with any timestamp, it is also essential for scoping your reports. You can create widgets that focus on a specific period, such as a sprint or a release cycle, by applying a filter like Created At in the previous 14 days.