Keypup

Dataset: Commits from pull requests

Description: The datetime at which the commit was created.

The <code>Created At</code> field from the Commits dataset is the precise timestamp for when a piece of code was saved, making it the fundamental unit for measuring the rhythm, volume, and patterns of your team's development activity.

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 <code>YEAR_MONTH(created_at)</code> and a <code>COUNT()</code> metric creates a classic "Commit Frequency" report, showing the volume of commits over time. This can also serve as a proxy for the DORA metric, Deployment Frequency, especially when filtered to a main branch.

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 <code>DAY_OF_WEEK(created_at)</code> or by the hour of the day with <code>HOUR(created_at)</code> 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 <code>Created At in the previous 14 days</code>.

- 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 <code>YEAR_MONTH(created_at)</code> and a <code>COUNT()</code> metric creates a classic "Commit Frequency" report, showing the volume of commits over time. This can also serve as a proxy for the DORA metric, Deployment Frequency, especially when filtered to a main branch.
- 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 <code>DAY_OF_WEEK(created_at)</code> or by the hour of the day with <code>HOUR(created_at)</code> 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 <code>Created At in the previous 14 days</code>.

Commits > Created at

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From:
Github (Commits)	`created_at`
Gitlab (Commits)	`created_at`
Bitbucket (Commits)	`date`
Azure DevOps (Commits)	`committer.date`
Jira	N/A
ClickUp	N/A
Trello	N/A

Commits > Created at

Reporting Use Cases