Historically, Metric Monitors supported bucketing data by hour and by day. We now also support bucketing by week and month, making it much easier to monitor sparse or infrequently updated data. For example, if a financial institution wants to do anomaly detection on data they get from an external partner once/month, that is now much easier to do than before.

In addition, when bucketing by week or month, the monitor now backfills much more historical data than before in order to understand seasonal trends. Up to 3 years of history is backfilled when bucketing by week, and up to 10 years when bucketing by month.

For customers with many warehouse integrations, in SQL monitors creation view, MC now automatically filter the warehouse list by domain, so users will only see the warehouses mapped to the assets in the domain selected on top.

3 new types of monitors are now available for the MC-Salesforce Data Cloud integration: metric monitor, validation monitor, comparison monitor.

See details and how to set up here https://docs.getmontecarlo.com/docs/salesforce-data-cloud#/

Advanced Monitors now fully support MySQL and Oracle, enabling customers to leverage Data Profiler and Monitoring Agent recommendations, as well as deploy metric, validation, and comparison monitors on their MySQL and Oracle assets.

Learn more about MySQL support

Learn more about Oracle support

MC can now observe Clickhouse! The MC-Clickhouse integration currently supports flexible custom SQL monitors and schema change detections. More capabilities will be added over time.
Docs: https://docs.getmontecarlo.com/docs/clickhouse#/

For customers on consumption pricing plans, Monte Carlo now sends an email summary of consumption once per month to all Account Owners. It includes detail from the previous month about credits consumed, credit rate ($), commit consumed ($), and amount due ($). This email is typically sent around the 5th of the month, but may be received off-cycle as well if you undergo a change in pricing plan.

It is possible to customize the recipient list of this email by clicking the Email statements button in the Current running statement section.

Monte Carlo now supports Salesforce CRM database! Current capabilities include SQOL rule monitor and schema change detection. More monitoring capabilities will be added over time.
More details and setup instruction here https://docs.getmontecarlo.com/docs/salesforce-crm

Salesforce Data Cloud is the widely adopted customer 360 data platform in Salesforce, which unifies data from various sources including data warehouses/lakes.

MC now supports SQL rule monitor and schema change detection for Salesforce Data Cloud. More capabilities like comparison monitor and metrics monitor will be added soon.

Follow docs here to set up the integration https://docs.getmontecarlo.com/docs/salesforce-data-cloud

For many of our customers who use SQL rules for data quality, getting a full list of all rows violating the rule is critical, as internal teams need to follow up on each and every one of them. When SQL rules were launched, we limited the number of rows to 500 per alert in order to constrain scale/complexity. This has just gotten a lot better! Users now have access to up to 5,000 rows when a SQL rule alerts.

Please note: requires reaching out to our support team to raise account level limits. The default remains 500 rows per alert.

For customers that use Redshift data sharing for sharing data between producer and consumer clusters, MC can now support lineage between such clusters and allow custom monitoring on each.

See docs here for more details