Abstract: A System and method for the application of in-memory analysis of network data applied to spatial market segmentation with demand estimates and competitor information comprising multiple data extractors, a descriptive module, a predictive module, a learning module, at least one application programming interface, and a visualization tool are disclosed. An example of network data is machine readable data that is acquired through an application programming interface. An example of in-memory analysis is the use of in-memory processing and storage objects. A descriptive module is configured to produce market features. An unsupervised learning module is configured to produce market segments and a visualization tool is configured to evaluate one or more market scenarios and to display market features with maps and charts.

Abstract: A System and method for the application of in-memory analysis of network data applied to logistics best facility recommendations with current market information comprising multiple data extractors, a descriptive module, a predictive module, a learning module, at least one application programming interface, and a visualization tool are disclosed. An example of network data is machine readable data that is acquired through an application programming interface. An example of in-memory analysis is the use of in-memory processing and storage objects. A descriptive module is configured to produce logistics network features. An unsupervised learning module is configured to produce logistics best facility recommendations and a visualization tool is configured to evaluate one or more logistics network scenarios and to display logistics network features with maps and charts.

Abstract: A System and method for the application of in-memory analysis of network data applied to site selection with current market information, demand estimates, and competitor information comprising multiple data extractors, a descriptive module, a predictive module, a learning module, at least one application programming interface, and a visualization tool are disclosed. An example of network data is machine readable data that is acquired through an application programming interface. An example of in-memory analysis is the use of in-memory processing and storage objects. A descriptive module is configured to produce market features. An unsupervised learning module is configured to produce site selection market segments and a visualization tool is configured to evaluate one or more market scenarios and to display market features with maps and charts.

Abstract: A System and method for the application of in-memory analysis of network data applied to profitability modeling with current market information comprising multiple data extractors, a descriptive module, a predictive module, a learning module, at least one application programming interface, and a visualization tool are disclosed. An example of network data is machine readable data that is acquired through an application programming interface. An example of in-memory analysis is the use of in-memory processing and storage objects. A descriptive module is configured to produce market features. An unsupervised learning module is configured to produce profitability models and a visualization tool is configured to evaluate one or more market scenarios and to display profitability features with maps and charts.