Target tenant resources

Users must have the COLEMANAI-User or the COLEMANAI-Administrator role to use and edit resources in the target tenant.

This table describes the resources that can be included in the global packages.


Resource	Category	Description	Restrictions
Dataset	Data collection	A dataset is the data that is used as input in a quest to build a model. The import in the target tenant includes the definition of the dataset from Infor Data Lake.	None
Groups	Data collection	The groups bind the multiple datasets together with a unique name. This is a mandatory step that is required for the successful import of the Optimization quest into the target tenant.	None
Quest	Machine learning	A quest is the flow of activities that build the machine learning model. The import in the target tenant includes the training and production quest definition.	None
Endpoint	Machine learning	An endpoint is the deployed machine learning model (REST API) that is invoked to get real-time predictions. The import in the target tenant includes the endpoint definition.	None
Custom Algorithm	Machine learning	A custom algorithm is a user-defined source code that is used as an algorithm to train a machine-learning model. The import in the target tenant includes the custom algorithm docker image and the source code files package.	None
Quest	Optimization	A quest is the flow of activities that build the optimization model. The import in the target tenant includes the design and production quest definition.	None
Endpoint	Optimization	An endpoint is the deployed optimization model (REST API) that is invoked to get real-time solutions. The import in the target tenant includes the endpoint definition.	None
Custom algorithm	Optimization	A custom algorithm is a user-defined source code that is used to solve the optimization problems. The import in the target tenant includes the custom algorithm docker image and the source code files package.	None