Abstract: Disclosed herein is a declarative modeling paradigm for a graph model, graph-physicalization, delta load/offload, automatic generation of sub-graphs based on user entitlements, a graph-pipeline for low-code graph file formats, and machine-learning pipeline for analysis of the graph model. In a particular aspect, a computer-implemented process includes generating a graphical user interface comprising one or more tools configured to allow a user to build and visualize a graph model based on data, obtaining the data from one or more sources, receiving input from the user via the graphical user interface, where the input comprises a request to create at least two nodes representing logical entities within the data and at least one edge representing one or more relationships between the logical entities, generating the graph model based on the input from the user, analyzing the data using the graph model, and output results based on the analyzing.

Abstract: Techniques for automatically deploying a version of a compute, both rule based and model based, with its dependencies when approved for deployment using one or more governance processes. One technique includes generating a compute fitting defined requirements and capable of executing on a defined model objective, generating a deployable archive bundle of the compute with dependencies based on a record of a lineage of the logical building blocks in dependency, analyzing performance of the compute with respect to a production compute deployed within a production environment, determining the performance of the compute is superior to the performance of the production compute based on the analyzing, and replacing the production compute in the production environment with the compute using the deployable archive bundle to facilitate deployment.

Abstract: Techniques for automatically deploying a version of a compute, both rule based and model based, with its dependencies when approved for deployment using one or more governance processes. One technique includes generating a compute fitting defined requirements and capable of executing on a defined model objective, generating a deployable archive bundle of the compute with dependencies based on a record of a lineage of the logical building blocks in dependency, analyzing performance of the compute with respect to a production compute deployed within a production environment, determining the performance of the compute is superior to the performance of the production compute based on the analyzing, and replacing the production compute in the production environment with the compute using the deployable archive bundle to facilitate deployment.

Abstract: Systems, methods, and other embodiments associated with introducing a new data structure to an executing application are described. In one embodiment, a method includes executing an application as an executing application to process data of a data structure maintained according to a data model. The example method may also include receiving a new data structure definition of a new data structure to define for the data model. The example method may also include performing impact analysis to determine whether the executing application is capable of processing data of the new data structure. The example method may also include updating the data model to include the new data structure definition to create an updated data model. The example method may also include generating control instructions to instruct the executing application to utilize data from the new data structure according to the updated data model.

Abstract: Systems, methods, and other embodiments associated with introducing a new data structure to an executing application are described. In one embodiment, a method includes executing an application as an executing application to process data of a data structure maintained according to a data model. The example method may also include receiving a new data structure definition of a new data structure to define for the data model. The example method may also include performing impact analysis to determine whether the executing application is capable of processing data of the new data structure. The example method may also include updating the data model to include the new data structure definition to create an updated data model. The example method may also include generating control instructions to instruct the executing application to utilize data from the new data structure according to the updated data model.