Jira project ‘status’ and Jira issue ‘issue type hierarchy level’ related columns available

[#1]

Hi, community!

We’re releasing new columns that will enable you to filter out archived or deleted Jira projects, group by issue type hierarchies, and more!

These columns will be available in both Atlassian Analytics and in data shares. We’ll gradually roll out the new columns over the next week.

New columns in the “Project” table

In the jira_project table, there are 3 new columns:

• Status - The current status of the project, which could be “active,” “archived,” or “deleted.”

• Created at - The date and time when the project was created.

• Updated at - The date and time when the project’s details were last edited.

More about the “Status” column

When a project is deleted or moved to the trash, the project will remain in the “Project” table for 60 days with a “deleted” status or until it is permanently deleted or restored. When the project is permanently deleted, it will stop appearing in the table.

When a project in an “archived” or “deleted” status is restored, its status will change back to “active.”

New columns in the Jira “Issue” table

Note about Jira terminology: “Issue” has changed to “Work item” in Jira. The display names in the Data Lake schema will change within the next few weeks, but the SQL names will remain the same.

In the jira_issue table (jira_issue_enhanced_table in data shares), there are 2 new columns:

• Issue type hierarchy level - The numeric value reflecting the issue type hierarchy that you’ve set for your Jira project. In most company-managed projects, Sub-task is -1, Story is 0, and Epic is 1.

• Issue type hierarchy name - The name you’ve given to each hierarchy level. Multiple issue types can share the same hierarchy level and name.

More columns for data shares

In addition to the above columns, the data share schema also has 2 new columns in the jira_issue_type table:

• hierarchy_name

• hierarchy_level

These columns contain the same information as the ones in the jira_issue_enhanced_table table. The duplicate information gives you the option to reduce joins, depending on the structure of your data model.

How to get the new columns

For Atlassian Analytics

An organization admin needs to edit the connections to add the new columns. If the Data Lake connection already includes Jira data, the organization admin can edit it and save it without making any changes. More about editing Data Lake connections.

For data shares

No action is required. You’ll start to see the new data flowing through them.

Tell us what you think

Comment below or contact support if you have any questions or concerns. Thanks!

[Josh]

Having this data available in the Data Share is very helpful for us. Thank you for the continued attention and development effort in this area!