Use a local data kit deployment to replicate Data Cloud metadata and process definitions
across multiple data spaces within the same sandbox org. Packaging configurations into a local
data kit reduces manual effort, ensures consistency, and accelerates time to value when your data
space strategy requires standardized definitions across different spaces. Standardization is
especially important for deployments across geographies or brands where processes are defined
centrally.
Required Editions
| Permission Sets Needed |
| To access Data Cloud Setup |
System admin profile OR
Data Cloud Architect permission set
|
Previously, replicating configurations such as calculated insights and segments required
manual re-creation in each data space, which was time-consuming and prone to error. With local
data kit deployment, Data 360 performs a pure upsert, automatically updating existing components
or creating new ones with the appropriate data space prefix.
- Verify that you're working in a Data 360 sandbox environment.
- Log in to the default data space.
- Make sure that your metadata and process definitions are finalized in the default data
space.
These high-level steps replicate metadata and promote it to production:
-
Create your data model objects (DMO) mappings, calculated insights, and segments in the
default data space of your sandbox.
-
Package your finalized configurations into a standard local data kit.
-
Use the one-click deployment for each target data space within the sandbox.
-
Add the necessary filters to the data lake objects (DLO) mapped into each of the target
data spaces.
-
Create a DevOps data kit for each data space to deploy the configurations to your
production environment.
