Abstract: The Multidimensional Machine Learning Data and User Interface Segment Tagging Engine Apparatuses, Methods and Systems (“MLUI”) transforms ambient condition data, sales data, user interface selections, cognitive intelligence question input inputs via MLUI components into project projections, campaigns, user interface visualizations, cognitive intelligence question output outputs. An update to a survey data file is detected. The updated survey data is stored in a SQL database configured to utilize a composite index of the updated survey data that optimizes database query time. A set of affected entity segment identifiers is determined. A set of affected category identifiers is determined. A set of affected cognitive intelligence (CI) datapoint identifiers is determined as CI datapoint identifiers associated with each combination of an affected entity segment identifier and an affected category identifier.

Abstract: The Multidimensional Machine Learning Data and User Interface Segment Tagging Engine Apparatuses, Methods and Systems (“MLUI”) transforms ambient condition data, sales data, user interface selections, cognitive intelligence question input inputs via MLUI components into project projections, campaigns, user interface visualizations, cognitive intelligence question output outputs. A category identifier selection is obtained via a category selection interaction interface mechanism. Entity segment identifier selections are obtained via entity segment selection interaction interface mechanisms. A set of visualization cognitive intelligence (CI) datapoint identifiers is determined as CI datapoint identifiers associated with each combination of a selected entity segment identifier and the selected category identifier.

Abstract: The Multidimensional Machine Learning Data and User Interface Segment Tagging Engine Apparatuses, Methods and Systems (“MLUI”) transforms ambient condition data, sales data, user interface selections, cognitive intelligence question input inputs via MLUI components into project projections, campaigns, user interface visualizations, cognitive intelligence question output outputs. A cognitive intelligence (CI) datapoint identifier cache datastructure is generated, the CI datapoint identifier cache datastructure configured to comprise a category identifier and an entity segment identifier. A CI datapoint value cache datastructure is generated, the CI datapoint value cache datastructure configured to comprise a set of module datastructures, each module datastructure corresponding to a module identifier associated with the category identifier, each module datastructure comprising a set of metric datastructures, each metric datastructure corresponding to a set of calculated metrics.