Data Models: Save Data Models Before Actually Deploying (decouple the functionalities)

This has got very frustrating as work on entering/updating our data models and it fails on deploy and all the changes have been lost.

### The ideal approach

**Save and Deploy should be TWO SEPARATE FUNCTIONALITIES**

Saving will save the structure of the models and deployment makes them live. It is idiotic and redundant to have them both in one single function with no history of changes or saves.

Also, when the deployment fails there is no error/reason message to say why the deployment failed.

Start by locating the data model editing and deployment entry points in the repository, since the issue names no files or tests. Define how saving model structure is separated from making it live, preserve changes when deployment fails, and expose a reason for deployment failure; completion should cover both workflows and their failure behavior.

Written by the indexing model from the issue text.