dbt snapshot and seed errors are now available in MC as alerts, alongside model and test alerts. Users can go to settings -> dbt integrations -> edit, to configure the option to send those alerts. Make sure to add the new alert types in the relevant audiences to receive notifications. (docs)

With the availability of SQL query history, a series of features for Databricks integration are added:

• Performance dashboard and monitors: the dashboard helps identify the slowest SQL queries and enables investigation on performance issues. Users can also use performance monitors to detect slow running SQL queries.
• Importance scores: estimates the importance (0 to 1) of assets based on various query history data (see details here).
• Usage stats: usage information like reads/day, writes/day, users etc are now available on the "assets" page, "general information" tab.
• Query logs: SQL query logs are now shown on the assets page
• Query Change RCA insights: associated SQL query changes are presented for a volume / freshness / field alert to help uncover query related root causes.

Limitations: note these features are available for assets on Unity Catalog and are constrained to SQL queries. If you are using customer-managed keys in Databricks, these features also will not be supported.

Setup required: In order to enable these features, read permission needs to be granted to the service principal for system table system.query.history. This is also described in docs here.

GRANT SELECT ON system.query.history TO <monte_carlo_service_principal>;

For many businesses, incoming data looks very different during major holidays. Maybe there is more or less data than normal, or the profile of that data is much different. For example, a financial technology firm may see less new data than normal on July 4, because markets are closed in the United States. Or an e-commerce company based in the United States may see more new data than normal on Black Friday, because it's one of the busiest shopping days of the year.

You can now easily use exclusion windows to Manage Holidays in order to:

• Remove the unusual holiday data from influencing machine learning thresholds
• Avoid receiving unwanted alerts during holidays

The available holidays include the 11 Federal Holidays within the United States, plus a few additional unofficial holidays that often influence data (e.g. Black Friday).

Users with an Editor role can now create their own Data Products and edit any Data Products they have previously created and are the owner for.

Users with Account Owner and Domain Manager roles continue to have permissions to create and edit all Data Products that have been created in the account.

For more on Managed Roles and Permissions, refer to https://docs.getmontecarlo.com/docs/authorization#managed-roles-and-groups

These operators make it easy to express a condition like "Alert me if the value returned by the SQL is not between 5 and 5,000." Previously, this would have needed multiple SQL Rules to express.

MC-Dremio integration is now available. Customers can run SQL monitor, comparison rules, and schema change detections on Dremio with MC. Both Dremio cloud and Dremio software are supported. Docs here https://docs.getmontecarlo.com/docs/dremio

dbt Job and model info are now overlaid on lineage. Job info is shown on lineage edges, model last run status and timestamp are shown on nodes.

Table and column tags are now automatically imported from Unity Catalog to Monte Carlo. Table tags will show up on Assets page, General Information tab, column tags will show up on Field Lineage tab. Make sure your data collector is updated to the latest version.

Monte Carlo now has a dedicated native app in the Microsoft Teams Store. It allows anomaly detections to be sent to any public channel in your workspace for quick triage and collaboration.

Learn more in the revamped Microsoft Teams integration documentation.

The data operations dashboard provides a look at team operational metrics:

• How quickly are we responding to alerts?
• How many incidents did we have and of what severity?
• How quickly are we resolving incidents?

The key changes around reporting on data operations are:

• Reporting on alerts marked as incidents rather than just alerts
• Drilling into dashboard content to see individual alerts and incidents
• Filtering an any grouping of alerts: Domains, Data products, Audiences, and Tags (monitor tags coming soon!)
• Ability to save custom dashboards based on filter sets you frequently visit

Learn more about metrics, filters, and saving dashboards in the Data operations (beta) documentation!

The data operations dashboard has replaced some of the content on the data reliability dashboard and the data reliability dashboard is being deprecated. Some of the content has moved to the Activity dashboard. If you have needs around deprecated content, please reach out here. This is a beta release.