Dataset: Activity Events
Entity: Activity Events
Field ID: created_at
Type: Datetime
Description: The datetime at which the event was created.
Note that this may not always reflect when the event is supposed to have occurred. For instance, it is common for users to set a date when submitting WORK_LOGGED events. This date is captured via the Value at field, which may be more suitable if you are looking at displaying events in chronological order of occurrence.
Source: Applications support the following events
Github:
CREATED,CLOSED,REOPENED,MERGED,REVIEWER_ASSIGNED,REVIEWER_UNASSIGNED,USER_ASSIGNED,USER_UNASSIGNEDGitLab:
CREATED,CLOSED,REOPENED,MERGED,REVIEWER_ASSIGNED,REVIEWER_UNASSIGNED,USER_ASSIGNED,USER_UNASSIGNED,WORK_LOGGEDBitbucket:
CREATED,CLOSED,MERGED,REVIEWER_ASSIGNED,REVIEWER_UNASSIGNEDAzure DevOps:
CREATED,CLOSED,MERGED,REVIEWER_ASSIGNED,REVIEWER_UNASSIGNEDJira:
CREATED,CLOSED,REOPENED,USER_ASSIGNED,USER_UNASSIGNED,WORK_LOGGED,WORKFLOW_STATUS_UPDATEDClickUp:
CREATED,CLOSED. ClickUp does not expose an events API. Keypup generates these two events based on the issue timestamps (date_created&date_closed)Trello:
CREATED,CLOSED,REOPENED,USER_ASSIGNED,USER_UNASSIGNED,WORKFLOW_STATUS_UPDATED
Transformation logic: N/A
From: |
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Github (Timeline Items) |
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Gitlab (Discussions, State Events) |
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Bitbucket (Activity) |
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Azure DevOps (PR Threads) |
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JIRA (Changelog, Worklog) |
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ClickUp (Issue timestamps) |
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Trello (Actions) |
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Reporting Use Cases
The Created At field from the Activity Events dataset is the timestamp that records the exact moment each event occurred. It is the fundamental time axis for this dataset, making it essential for creating historical trend reports, activity feeds, and cumulative flow diagrams.
Filtering for Time-Based Analysis: Its most common use is to scope your analysis to a specific time period.
To create an activity feed for a daily stand-up, you can use a filter like
Created At in the previous 24 hours.To review all the workflow changes that happened last quarter, you would filter where
Created At in the previous quarter.
Reporting on Activity Volume: When used as a dimension, this field allows you to visualize the frequency and trends of different activities over time.
You can create a line chart with a dimension like
YEAR_MONTH(created_at)and a metric likeCOUNT_IF(action == "MERGED")to track the number of merges per month.
Enabling Historical State Reconstruction: This is the most powerful use case for this field. It provides the chronological order needed to build cumulative charts that reconstruct the state of your system at any point in the past.
To build a chart showing the total number of open issues over time, you need a time-series dimension like
YEAR_MONTH(created_at)and a cumulative metric that adds or subtracts based on the event type:SUM_CUMULATIVE(IF(CONTAINS(["CREATED", "REOPENED"], action), 1, -1)). This calculation is entirely dependent on theCreated Atfield to provide the correct sequence of events.