An issue is generated when a metric starts alerting. When an issue is created, it is the first time a metric run is deemed to be anomalous and every subsequent run that falls outside of threshold bounds while an issue is still open is an alert on that issue.
Issues enable data teams to resolve data quality issues faster and more effectively by threading data quality alerts into a single timeline with valuable context on related issues, past remediation, and the current status of the issue. Issues can be accessed from anywhere in the Bigeye platform, including the catalog or when viewing a collection, making it easy to document past fixes and speed up future resolution. Issues help data teams more effectively resolve data quality issues with
- Threaded notifications: Alerts related to the same metric are aggregated into a single issue.
- Faster resolution: Manage issues — acknowledge, resolve, and close — with a single click.
- Smarter alerts: Mark alerts as good or bad to help improve anomaly detection over time.
- Swifter action: Leave notes and context on closed issues to help your team resolve similar issues faster the next time.
- Find related issues: View the previous issues for the same metric to find a quick fix for existing issue.
- View data lineage for the current issue.
- Debug: Use metric query and debug query in your source to help troubleshoot your current issue.
To learn more about how to view the list of issues, see View Issues.
Updated about 1 month ago