Dynamically generating consumption artifacts for platforms using independent processing of usage event data streams

A system for dynamically generating consumption artifacts for platforms using independent processing of usage event data streams, comprising:

• a memory that stores a set of instructions;
• and
• a processor that is configured to execute the set of instructions for:
• obtaining usage event data streams through calls to an application programming interface (API) securely via the internet, wherein the usage event data streams include a unit of measure, a quantity, and a date and time of occurrence;
• updating, using a processor, a technical lifecycle event map based on the usage event data streams;
• initializing multiple distinct time streams of consumption impacts at a configurable time stream interval that represents a slice of time within the time stream and specific usage event data associated with the time stream, wherein the time streams comprise pricing timestreams, rating time streams, and invoicing time streams that are processed independently and can operate in real-time or non-real-time;
• processing, on a distributed computer architecture, an independent logic for each category of time stream of consumption, wherein at least one processing step of the independent logic is executed on a different computer;
• invoking specific algorithms and data models for a plurality of computation modules to process each consumption event in real-time across multiple timestreams;
• dynamically updating the technical lifecycle event map and associated consumption artifacts;
• and
• mapping the processed technical data to predefined technical structures using a headless API to dynamically generate a set of consumption artifacts that are associated with usage consumptions to transmit to an external system securely via the internet.

A non-transitory computer-readable storage medium storing a sequence of instructions, which when executed by one or more processors, causes deriving a subset from a dataset based on proclivity of entity devices towards a category, comprising:

• obtaining usage event data streams through calls to an application programming interface (API) securely via the internet, wherein the usage event data streams include a unit of measure, a quantity, and a date and time of occurrence;
• updating, using a processor, a technical lifecycle event map based on the usage event data streams;
• initializing multiple distinct time streams of consumption impacts at a configurable time stream interval that represents a slice of time within the time stream and specific usage event data associated with the time stream, wherein the time streams comprise pricing timestreams, rating time streams, and invoicing time streams that are processed independently and can operate in real-time or non-real-time;
• processing, on a distributed computer architecture, an independent logic for each category of time stream of consumption, wherein at least one processing step of the independent logic is executed on a different computer;
• invoking specific algorithms and data models for a plurality of computation modules to process each consumption event in real-time across multiple timestreams;
• dynamically updating the technical lifecycle event map and associated consumption artifacts;
• and
• mapping the processed technical data to predefined technical structures using a headless API to dynamically generate a set of consumption artifacts that are associated with usage consumptions to transmit to an external system securely via the internet.