Multidimensional machine learning data and user interface segment tagging engine apparatuses, methods and systems

A cognitive intelligence visualization engine processor-readable, non-transient medium, comprising processor-executable instructions configured to:

• obtain, via at least one processor, a category identifier selection via a category selection interaction interface mechanism;
• obtain, via at least one processor, a first entity segment identifier selection via a first entity segment selection interaction interface mechanism;
• obtain, via at least one processor, a second entity segment identifier selection via a second entity segment selection interaction interface mechanism;
• determine, via at least one processor, a set of visualization cognitive intelligence (CI) datapoint identifiers, the set of visualization CI datapoint identifiers configured to include CI datapoint identifiers associated with each combination of:
• a selected entity segment identifier and the selected category identifier;
• retrieve, via at least one processor, for each CI datapoint identifier in the set of visualization CI datapoint identifiers, a CI datapoint value corresponding to the respective CI datapoint identifier from a NoSQL database via a cache datastructure, the NoSQL database configured to act as cache for generating visualizations based on metrics calculated using survey data, a cache datastructure configured as a key-value pair comprising an associated CI datapoint identifier and a CI datapoint value corresponding to the associated CI datapoint identifier;
• generate, via a cache datastructure via at least one processor, a visualization using the retrieved CI datapoint values, the visualization configured to display a set of metrics, for a set of utilized allowable response question identifiers associated with the selected category identifier, for each selected entity segment identifier.

A cognitive intelligence visualization engine processor-implemented system, comprising:

• means to process processor-executable instructions;
• means to issue processor-issuable instructions from a processor-executable component collection via the means to process processor-executable instructions, the processor-issuable instructions configured to:
• obtain, via at least one processor, a category identifier selection via a category selection interaction interface mechanism;
• obtain, via at least one processor, a first entity segment identifier selection via a first entity segment selection interaction interface mechanism;
• obtain, via at least one processor, a second entity segment identifier selection via a second entity segment selection interaction interface mechanism;
• determine, via at least one processor, a set of visualization cognitive intelligence (CI) datapoint identifiers, the set of visualization CI datapoint identifiers configured to include CI datapoint identifiers associated with each combination of:
• a selected entity segment identifier and the selected category identifier;
• retrieve, via at least one processor, for each CI datapoint identifier in the set of visualization CI datapoint identifiers, a CI datapoint value corresponding to the respective CI datapoint identifier from a NoSQL database via a cache datastructure, the NoSQL database configured to act as cache for generating visualizations based on metrics calculated using survey data, a cache datastructure configured as a key-value pair comprising an associated CI datapoint identifier and a CI datapoint value corresponding to the associated CI datapoint identifier;
• generate, via a cache datastructure via at least one processor, a visualization using the retrieved CI datapoint values, the visualization configured to display a set of metrics, for a set of utilized allowable response question identifiers associated with the selected category identifier, for each selected entity segment identifier.

A cognitive intelligence visualization engine processor-implemented process, comprising executing processor-executable instructions to:

• obtain, via at least one processor, a category identifier selection via a category selection interaction interface mechanism;
• obtain, via at least one processor, a first entity segment identifier selection via a first entity segment selection interaction interface mechanism;
• obtain, via at least one processor, a second entity segment identifier selection via a second entity segment selection interaction interface mechanism;
• determine, via at least one processor, a set of visualization cognitive intelligence (CI) datapoint identifiers, the set of visualization CI datapoint identifiers configured to include CI datapoint identifiers associated with each combination of:
• a selected entity segment identifier and the selected category identifier;
• retrieve, via at least one processor, for each CI datapoint identifier in the set of visualization CI datapoint identifiers, a CI datapoint value corresponding to the respective CI datapoint identifier from a NoSQL database via a cache datastructure, the NoSQL database configured to act as cache for generating visualizations based on metrics calculated using survey data, a cache datastructure configured as a key-value pair comprising an associated CI datapoint identifier and a CI datapoint value corresponding to the associated CI datapoint identifier;
• generate, via a cache datastructure via at least one processor, a visualization using the retrieved CI datapoint values, the visualization configured to display a set of metrics, for a set of utilized allowable response question identifiers associated with the selected category identifier, for each selected entity segment identifier.