A device for analyzing data with computer vision, comprising: a processor and a memory, said memory comprising program instructions that, when executed, cause the processor to: create a series of correlated pictographs wherein each pictograph in the series of correlated pictographs is generated by: receiving a plurality of metrics associated with a system; generating a raw data pictograph that schematically represents the plurality of metrics; identifying from the plurality of metrics at least two metrics that have relational significance, wherein the at least two metrics have relational significance when a mathematical relationship exceeding a probability relationship threshold exists between the at least two metrics; and creating a correlated pictograph comprising the at least two metrics; analyse, using computer vision, the series of correlated pictographs to determine a mathematical relationship of the metrics; create a baseline pictograph stack comprising the series of correlated pictographs based on the mathematical relationship wherein: each correlated pictograph represents system metrics at a specific moment in time; and the baseline pictograph stack indicates how the at least two metrics relate to each other during acceptable operating conditions; obtain a plurality of real time metrics associated with the system; create a real time pictograph that schematically represents the real time metrics associated with said system; compare, using computer vision, said baseline pictograph stack with said real time pictograph to determine whether the real time metrics are within acceptable operating parameters; and notify the system that there is an issue if the real time metrics are not within acceptable operating parameters. create a series of correlated pictographs wherein each pictograph in the series of correlated pictographs is generated by: receiving a plurality of metrics associated with a system; generating a raw data pictograph that schematically represents the plurality of metrics; identifying from the plurality of metrics at least two metrics that have relational significance, wherein the at least two metrics have relational significance when a mathematical relationship exceeding a probability relationship threshold exists between the at least two metrics; and creating a correlated pictograph comprising the at least two metrics; receiving a plurality of metrics associated with a system; generating a raw data pictograph that schematically represents the plurality of metrics; identifying from the plurality of metrics at least two metrics that have relational significance, wherein the at least two metrics have relational significance when a mathematical relationship exceeding a probability relationship threshold exists between the at least two metrics; and creating a correlated pictograph comprising the at least two metrics; analyse, using computer vision, the series of correlated pictographs to determine a mathematical relationship of the metrics; create a baseline pictograph stack comprising the series of correlated pictographs based on the mathematical relationship wherein: each correlated pictograph represents system metrics at a specific moment in time; and the baseline pictograph stack indicates how the at least two metrics relate to each other during acceptable operating conditions; obtain a plurality of real time metrics associated with the system; each correlated pictograph represents system metrics at a specific moment in time; and the baseline pictograph stack indicates how the at least two metrics relate to each other during acceptable operating conditions; create a real time pictograph that schematically represents the real time metrics associated with said system; compare, using computer vision, said baseline pictograph stack with said real time pictograph to determine whether the real time metrics are within acceptable operating parameters; and notify the system that there is an issue if the real time metrics are not within acceptable operating parameters.