Help distinguish the criticality of SQL rule breaches by pre-setting the severity. This can be set in the SQL rule wizard, so all incidents from that rule inherit the severity.

in the dbt tab of the Incident IQ page for each dbt run result.

Want to link a runbook or @mention a user or group to drive faster time-to-resolution? In the notes of custom monitors, or the custom message of Notification Settings, you can now @mention user groups, format links, and more using Slack's format guide.

In the notes of a SQL Rule, you can use {{query\_result:field\_name}} to parameterize values from the query into a notification, replacing field\_name with the desired column. The values will show as a comma separated list. For example, if you have a SQL Rule looking for Salesforce Opportunities with wonky data, you can now include the opportunity\_id of the bad opportunities directly in the notification.

Notifications in Slack contain a message at the bottom informing users that thread replies get sync'd back to the MC app. This is included by default for compliance reasons, but many customers have asked for the option to remove it. This toggle makes it easy to remove the 'Note' across all your MC notifications in Slack. Find it on Settings > Integrations > Slack

For volume anomalies, we now show a "Correlation Analysis" tab on the Incident IQ page for each anomaly. In addition to showing high correlations found as previously available, we now surface low correlations found, as well as results when the analysis was not successful or eligible.

In the Query Logs section of both Incident IQ and Catalog pages, the queries table now has new columns showing query type, runtime, and query preview. For rows with multiple queries, the runtime is the average of all included queries.

Each table lineage widget now has a fullscreen toggle to maximize the lineage graph on the screen, allowing more nodes to be visible on the screen at once.

Users can now snooze any dbt model error or test failure via incident feed or incident IQ.

To significantly improve the performance and reduce query costs of our ML powered monitors (Field Health and Dimension Tracking), we now can automatically detect partitions in Data Lake deployments.

When detected, the partition can be enabled in the Advanced section