Systems and methods for a framework for algorithmically identifying critical software systems and applications within an organization

A method of generating real-time notifications of software application importance based on current processing requirements in a disparate computer network, the method comprising:

• receiving a first data set, wherein the first data set comprises a first amount of traffic attributed to computational processes executed by a plurality of applications, wherein the first amount of traffic comprises a respective amount of traffic amount of traffic for a plurality of processing requirements;
• receiving a second data set, wherein the second data set comprises second amount of traffic, wherein the second amount of traffic comprise a respective amount of traffic for a plurality of applications;
• receiving a third dataset, wherein the third dataset comprises dependencies between the plurality of processing requirements and the plurality of applications;
• determining a set of many-to-many relationships between each of the plurality of processing requirements and each of the plurality of applications based on the dependencies;
• inputting the set of many-to-many relationships into a model to identify respective importance metrics for each of the plurality of applications, wherein machine learning is trained to determine importance metrics based on a number of relationships, in the set of many-to-many relationships, for a given application and a amount of traffic for the given application;
• and
• generating for display, on a user interface of a user device, a ranking of the plurality of applications based on the respective importance metrics.

A non-transitory computer readable medium having instructions recorded thereon that when executed by one or more processors cause operations comprising:

• receiving a first data set, wherein the first data set comprises first amount of traffic, wherein the first amount of traffic comprise a respective amount of traffic for a plurality of processing requirements;
• receiving a second dataset, wherein the second dataset comprises second amount of traffic, wherein the second amount of traffic comprise a respective amount of traffic for a plurality of applications;
• receiving a third dataset, wherein the third dataset comprises a dependencies between the plurality of processing requirements and the plurality of applications;
• determining a set of many-to-many relationships between each of the plurality of processing requirements and each of the plurality of applications based on the dependencies;
• inputting the set of many-to-many relationships into a model to identify respective importance metrics for each of the plurality of applications, wherein machine learning is trained to determine importance metrics based on a number of relationships, in the set of many-to-many relationships, for a given application and a amount of traffic for the given application;
• and
• generating for display, on a user interface of a user device, a ranking of the plurality of applications based on the respective importance metrics.