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Known Limitations

What to expect during EAP?

Atlassian’s analytics offering gives you access to the Atlassian Data Lake and powerful dashboard-building functionality. We believe the Data Lake will help you unlock additional value from your Atlassian products through easier and more complete access to data for reporting purposes. As we begin bringing our analytics capabilities to market, changes may still occur with our data and permissions model. Because of this, we recommend the following:

  • Do not rely on the Data Lake as a production-level data source yet

  • Only roll out our analytics offering to a small group of people in your organization (and have them join this private Community group to stay up-to-date on new features and changes).

When our analytics capabilities are released for General Availability (GA), that’s the time to share it with your whole organization.

Known limitations

Data in the Data Lake

  • Product data

    Currently only data for Jira Software, Jira Service Management, Jira Work Management, and Opsgenie are available in the Data Lake. We’re working to add data for more products soon. If there are specific products you’d like to see next, let us know in the comments.

    While the Data Lake will hold the majority of your Jira data, not all data will be reflected in the Data Lake, such as specific custom fields. We’d appreciate your feedback on additional fields you’d like included in the data model, as we continue to actively evolve it.
  • User data

    User info such as email, account id, and name may be found in the Account table. However, at this time only data from managed accounts are included.

Data permissions

The Data Lake is an Analytics data source. As such, connections do not reflect product permissions. Remember, whoever has access to a Data Lake connection can browse all the data scoped in that connection. During the early part of the EAP, we suggest you limit access to the Data Lake if you have sensitive data in there.

Editing Data Lake connections

Editing existing Data Lake connections is currently unavailable. We plan to bring this as soon as possible. In the meantime, if you need to add or remove product data from a connection, you’ll need to create a new one and update your queries accordingly to use the new connection.

Similarly, you’ll need to create a new connection if you’d like to include data for projects that were created after your Data Lake connection was created. Only the projects that existed when you created the connection are included.

Data model changes

We welcome feedback from our EAP customers about the data model. Please be mindful that based on that feedback we may introduce breaking changes into the data model during EAP that may require you to update the queries or charts you have built to the revised schema. We will always post updates in the private Community Group so that is the best place to keep updated on upcoming changes. Once we reach GA, breaking changes will be managed like changes to an API and will be done very sparingly.

Changes in some Jira fields may not (yet) be 100% consistent in the Data Lake

Since our analytics capabilities are still in private beta, you may find that certain fields, or issues, may not be up to date in the Data Lake. If you experience any inconsistencies between the data in the Data Lake and your Jira data, please notify our team as soon as possible so we address it as soon as possible.

Custom fields

We currently don’t support all custom field types in the Data Lake, but we’re working to add more over time. You can query your custom fields using the jira_issue_field table.

Some fields from your issue history data may result in NULL records

If your issue history data refers to deleted statuses, deleted issue types, or other information that is no longer available, this may result in null records for fields that could not be resolved, such as the status category for a deleted status. This can also affect derived fields like the issue cycle time. In the absence of status category data, you can use status information directly to calculate cycle time.

Incorrect request type for Jira Service Management issues

When you change an issue type for an issue and there's no request type associated with the updated issue, the data in the Data Lake may show an incorrect request type for that issue. To fix this problem, you'll need to enable the Default request type feature so a request type is always added whenever the issue type of an issue changes.

Deleted Jira records still exist in the Data Lake

If you delete a Jira issue or project, for instance, the record will still show up in query results in Atlassian Analytics. We recognize this affects the data you see on your dashboards, so our team is looking to resolve this soon.

Language other than our default (English) is not yet available for early access

For example, Jira Software proprietary data such as field names and field values in German will not appear in German in the Data Lake, and when queried. Custom fields will, however, be in your language.

If you’ve identified an issue or limitation that’s not listed here, please raise it in the comments below!

2 comments

Hi,

The product looks really nice and already looking forward to be able edit a data lake connection.

As we are all aware that a connection will be containing too much or too little information for reporting, appending the scope of reporting, based on projects, but more likely on specifics.

As we want to keep are connections scoped to the relevant data.

Cheers,

Marc

Esther Strom Community Leader May 12, 2022

Known limitation at this time: sprint data doesn't exist yet. Documented here.

Also Jira usage metadata, although that was never actually promised.

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