Auxiliary query commands to deploy predictive data models for queries in a networked computing platform

A system comprising:

• a memory including executable instructions of one or more applications;
• and
• a processor, responsive to executing the instructions, is configured to:
• access, by a query engine, subsets of dataset data from a plurality of data repositories;
• apply, by the query engine, the subsets of dataset as input data to model generator applications, each model generator application configured to apply one or more machine learning algorithms or deep learning algorithms to train a predictive data model to predict degrees of confidence data as resultant output data;
• associate, by the query engine, the predicted data model to an in-situ auxiliary query command;
• cause access via a network to data representing one or more portions of an application stack distributed among computing cloud-based resources, the one or more portions of the application stack configured to implement computerized tools to automatically deploy predictive data models based on in-situ auxiliary query commands;
• and
• identify via the network a request to perform a query, the one or more portions of the application stack configured to perform data operations, the processor further configured to:
• detect a query request associated with the query including the in-situ auxiliary query command, the in-situ auxiliary query command being configured to implement the predictive data model;
• identify data representing the predictive data model for transmission to a query layer of the application stack, the predictive data model associated with the in-situ auxiliary query command;
• serialize the predictive data model for transmission as a serialized predictive data model into one or more byte or bit streams;
• cause presentation of user inputs to a user interface configured to perform the query responsive in association with the query request;
• receive query data referencing parameters, a dataset, and the predictive data model;
• execute one or more queries based on the query associated with data configured to access at least a portion of a graph data arrangement being formatted as triple-based data;
• identify resultant data including data representing a degree of confidence relative to the predictive data model used to determine the resultant data;
• format subsets of the resultant data and corresponding data representing degrees of confidence in tabular data format;
• and
• cause presentation of the tabular data format at the user interface.