Error parameter generation and utilization for data projections in a computing storage network

A system for error parameter generation and utilization for data projections in a computing storage network, the system comprising:

• one or more hardware computing system processors;
• and
• at least one memory storing instructions, that when executed by the one or more hardware computing system processors causes the one or more hardware computing system processors to:
• activate a computing storage network, the computing storage network being communicatively connected to:
• a computing model repository,
• a metric data repository, and
• a record repository that is external to the computing storage network;
• determine or access a first computing model comprised in the computing model repository;
• determine or access first data comprised in the metric data repository;
• generate, based on the first computing model and based on the first data comprised in the metric data repository, first projected data;
• format the first projected data to have one or more of:
• a first type of granularity, or a second type of granularity, or a third type of granularity, or a fourth type of granularity, or a fifth type of granularity;
• determine or access a second computing model associated with the computing model repository;
• determine or access the first data comprised in the metric data repository and second data comprised in the record repository that is external to the computing storage network;
• generate, based on the second computing model and based on the first data comprised in the metric data repository and the second data comprised in the record repository that is external to the computing storage network, second projected data;
• format the second projected data to have one or more of:
• the first type of granularity, or the second type of granularity, or the third type of granularity, or the fourth type of granularity, or the fifth type of granularity;
• determine or access a third computing model comprised in the computing model repository;
• determine or access third data comprised in the metric data repository;
• generate, based on the third computing model and the third data, third projected data;
• format the third projected data to have one or more of:
• the first type of granularity, or the second type of granularity, or the third type of granularity, or the fourth type of granularity, or the fifth type of granularity;
• determine, based on the second data comprised in the record repository that is external to the computing storage network, an error parameter associated with the first projected data, the second projected data, and the third projected data;
• rank, based on the error parameter, the first projected data, the second projected data, and the third projected data;
• select, based on the ranking, at least one of the first projected data, the second projected data, and the third projected data;
• and
• generate, based on selecting one of the first projected data or the second projected data or the third projected data, a digital report wherein the digital report indicates:
• dispensing projection data of a first configurable data object associated with a first set of user categories, a second set of user categories, or a third set of user categories, and
• protocol projection data or procedure projection data associated with the
• first set of user categories, the second set of user categories, or the third set of user categories.

A method for error parameter generation and utilization for data projections in a computing storage network, the method comprising:

• activating, using one or more computing device processors, a computing storage network, the computing storage network being communicatively connected to:
• a computing model repository,
• a metric data repository, and
• a record repository that is external to the computing storage network;
• determining or accessing, using the one or more computing device processors, a first computing model comprised in the computing model repository;
• determining or accessing, using the one or more computing device processors, first data comprised in the metric data repository;
• generating, using the one or more computing device processors, based on the first computing model and based on the first data comprised in the metric data repository, first projected data;
• formatting, using the one or more computing device processors, the first projected data to have one or more of:
• a first type of granularity, or a second type of granularity, or a third type of granularity, or a fourth type of granularity, or a fifth type of granularity;
• determining or accessing, using the one or more computing device processors, a second computing model associated with the computing model repository;
• determining or accessing, using the one or more computing device processors, the first data comprised in the metric data repository and second data comprised in the record repository that is external to the computing storage network;
• generating, using the one or more computing device processors, based on the second computing model and based on the first data comprised in the metric data repository and the second data comprised in the record repository that is external to the computing storage network, second projected data;
• formatting, using the one or more computing device processors, the second projected data to have one or more of:
• the first type of granularity, or the second type of granularity, or the third type of granularity, or the fourth type of granularity, or the fifth type of granularity;
• determining or accessing, using the one or more computing device processors, a third computing model comprised in the computing model repository;
• determining or accessing, using the one or more computing device processors, third data comprised in the metric data repository;
• generating, using the one or more computing device processors, based on the third computing model and the third data, third projected data;
• formatting, using the one or more computing device processors, the third projected data to have one or more of:
• the first type of granularity, or the second type of granularity, or the third type of granularity, or the fourth type of granularity, or the fifth type of granularity;
• determining, using the one or more computing device processors, based on the second data comprised in the record repository that is external to the computing storage network, an error parameter associated with the first projected data, the second projected data, or the third projected data;
• ranking, using the one or more computing device processors, based on the error parameter, the first projected data, the second projected data, and the third projected data;
• selecting, using the one or more computing device processors, based on the ranking, one or more of the first projected data, the second projected data, and the third projected data;
• and
• generating, using the one or more computing device processors, based on selecting one of the first projected data or the second projected data or the third projected data, a digital report, wherein the digital report indicates one or more of:
• dispensing projection data of a first configurable data object associated with a first set of user categories, a second set of user categories, or a third set of user categories, and
• protocol projection data or procedure projection data associated with the first set of user categories, the second set of user categories, or the third set of user categories.