In the performance dashboard, if users click into any query details drawer for a write query, two additional charts are added alongside the run time chart and volume chart: i) partitions scanned v.s. total partition chart, ii) % scanned from cache. These are available for Snowflake accounts.

SELECT/read queries are now live in a new view called "Read Queries" in the Performance dashboard! With this feature, you'll be able to easily identify the slowest running queries across your org and use the filters to investigate particular subsets further.

drill in from models to associated query details.

Please see demo video and docs.

All customers with dbt integration can find the gantt view available in assets page. To associate queries to dbt jobs/models, follow tagging instructions here for dbt core, and here for dbt cloud.

Users sending notifications to MS Teams now can turn off the ‘Normalized’ messages in Notification Settings. Unlike in Slack where ‘Normalized’ messages get threaded with their original notification, in MS Teams, the ‘Normalized’ messages get sent as entirely new messages. The current state of our integration to MS Teams does not allow threading. In some cases, these standalone ‘normalized’ messages were perceived as noisy and this option now lets users turn them off.

for Field Health now show in the Field Health charts. They show as a gray shadow overlaid on the chart, as well as in the tooltip when hovering over the chart. You'll see these thresholds both in graphs on IncidentIQ and when looking at the 'Results' section of a Field Health Monitor.

• Lookback Range - you can now select a specific date range or use the suggested presets

For more details on the Data Reliability Dashboard, refer to our docs.

Users can now write a SQL Query that defines the list of allowed and never-missing values in a Cardinality Rule. This makes it much easier to scale and build resilient Cardinality Rules, since the query can automatically compensate for when new values need to be added. Plus, for large numbers of values, it is much easier to write a query than to input them individually.

Users can now import meta fields from dbt as tags in MC.

Hourly metadata collection jobs can now be run through SQL Warehouses. Previously, collection could only be run through Spark clusters. This has benefits to deployment simplicity as well as potential cost-savings and performance gains.

A new section now exists in the Custom Monitor menu called Templates, where users can create, save, and edit custom templates for SQL Rules. This allows you to build a library of SQL Rule templates that are specific to your business.