Keeping your namespace consistent when you are using tools that pull from the same source is a great way to get richer context for your data
Namespaces are used in data engineering to organize and group related objects, such as tables, views, functions, and procedures, into a logical unit. This helps to avoid naming collisions and makes it easier to manage and reference the objects.
Grai is no different, namespaces are the primary method used to group your data lineage structure. For instance if you are pulling data from a dbt and Snowflake connection which run on the same Snowflake instance, you don't want to accidentally duplicate your nodes. To ensure metadata from both sources overlap you can use the "Namespace" field. Allowing Grai to intelligently map metadata from each source on top of each other. Checkout the Enhanced dbt Test example to see the power of namespaces in action.