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.

You can now click a button on the Monte Carlo UI to upgrade your collector! No need to download anything or setup local profiles. Moreover, the AWS CloudFormation template is viewable and share-able from the UI.

See the docs here: https://docs.getmontecarlo.com/docs/upgrading-the-data-collector

We are live on a new continent! Monte Carlo now spans 13 regions across 5 continents.

When in the Airflow application and adding a connection back to Monte Carlo:

• First, install the airflow provider: https://pypi.org/project/airflow-mcd/
• Then, you can now select the "Monte Carlo Data" connection type. This allows you to use the new test feature in Airflow to confirm that their token is valid, service user permissions are correct, and that Monte Carlo is reachable when using circuit breakers or our Airflow observability and incidents integration.

Field health anomalies on numeric fields like mean, percentiles, etc. will now also have correlation insights to assist the root cause analysis. The insights will visualize the impact on mean, percentile metrics from both the row count and field value of the anomalous rows.