As part of a data governance strategy, tags may be used to organize and classify data assets. Tags are typically key-value pairs that are used to attach information, like metadata, to an asset. Tags can be used to logically group assets in a way that is meaningful to your organization.
Tags can be applied directly in Monte Carlo from a data asset’s Catalog page using the UI, or via the API. They can also be applied to data assets within the source systems, for example see the Snowflake documentation around tags.
While not enabled by default, tags can be imported into Monte Carlo from your data sources where applicable. If you are interested in having tags imported from your data sources into Monte Carlo, please let us know!
When tag import is enabled, we will collect tags from your data sources via metadata, or in the case of dbt, from the
When a tag has been imported from a source system, it will be indicated on the tag.
Frequently Asked Questions
How long does it take for a tag that was added to a data asset in the data source, to show up in Monte Carlo catalog?
Metadata collection happens hourly, so if you add a new tag to a data asset, it could take some time to see the new tag in the Monte Carlo catalog.
Where are tags retrieved from in Snowflake?
The data collector retrieves tags from the
SNOWFLAKE.ACCOUNT_USAGE.TAG_REFERENCES table in Snowflake.
Will tags that have been added to Monte Carlo directly be overwritten by tags that are imported from a data source?
No, tags imported from a data source are appended to the tags added directly to Monte Carlo. If a tag exists in a data source with the same KEY name of a tag that has been added directly to Monte Carlo, the one added to Monte Carlo directly will take precedence.
If I delete a tag from a table in the data source, will it be removed from Monte Carlo?
Yes! If a tag that has been imported from a data source into Monte Carlo is removed, the change will be synced to Monte Carlo and the tag will be removed.
Updated about 2 months ago