Data Products to ensure monitoring coverage

Defining a Data Product now tags all assets and their upstream tables with a tag in Monte Carlo. This tag can be monitored in the Usage UI to ensure monitoring coverage for that Data Product.

This provides a better way to define these "use cases", "workloads", "workflows", etc. that deliver some collection of trusted data. Once a Data Product is defined, all related upstream tables are automatically tagged by Monte Carlo and can be monitored in the Usage UI, ensuring full monitoring coverage for the Data Product. This allows you to focus on monitoring these larger "workloads" that are important to your business, vs having to hunt around for individual tables to include in monitoring one-at-a-time.

How does it work?

1. Define the Data Product - When defining a Data Product, you should think about including the "interfaces" that make up your Data Products. These are the BI Report or the tables that users, APIs, or other data consumers are reading from.
2. Monte Carlo tags all upstream tables - Once the assets are included and the Data Product is saved, Monte Carlo will automatically look upstream using lineage to tag all tables that are connected to those assets defined in the Data Product.
3. Add a rule to monitor the tag - You can then choose to monitor all tables with that tag from the Data Product. This will ensure that all tables that relate to that Data Product are monitored by Monte Carlo.
4. See coverage overview and same great dashboard - The Data Product provides an overview of its monitoring coverage and a dashboard to see current incidents.

See a full video walkthrough: