Abstract: According to some embodiments, an analytics computing environment data store may contain a set of electronic data records, each electronic data record being associated with a predictive analytic algorithm and including an algorithm identifier and a set of algorithm characteristic values. An analytics environment computer may receive an adjustment from a user associated with an enterprise, the adjustment changing at least one of the set of algorithm characteristic values for a predictive analytic algorithm. Deployment of the predictive analytic algorithm may then be initiated in an enterprise operations workflow and at least one result may be generated. The deployed predictive analytic algorithm may then monitor the result and generate an alert signal when the result exceeds a boundary condition.

Abstract: According to some embodiments, an analytics computing environment data store may contain a set of electronic data records, each electronic data record being associated with a predictive analytic algorithm and including an algorithm identifier and a set of algorithm characteristic values. An analytics environment computer may receive an adjustment from a user associated with an enterprise, the adjustment changing at least one of the set of algorithm characteristic values for a predictive analytic algorithm. Deployment of the predictive analytic algorithm may then be initiated in an enterprise operations workflow and at least one result may be generated. The deployed predictive analytic algorithm may then monitor the result and generate an alert signal when the result exceeds a boundary condition.

Abstract: According to some embodiments, an analytics computing environment data store may contain a set of electronic data records, each electronic data record being associated with a predictive analytic algorithm and including an algorithm identifier and a set of algorithm characteristic values. An analytics environment computer may receive an adjustment from a user associated with an enterprise, the adjustment changing at least one of the set of algorithm characteristic values for a predictive analytic algorithm. Deployment of the predictive analytic algorithm may then be initiated in an enterprise operations workflow and at least one result may be generated. The deployed predictive analytic algorithm may then monitor the result and generate an alert signal when the result exceeds a boundary condition.

Abstract: According to some embodiments, an analytics computing environment data store may contain a set of electronic data records, each electronic data record being associated with a predictive analytic algorithm and including an algorithm identifier and a set of algorithm characteristic values. An analytics environment computer may receive an adjustment from a user associated with an enterprise, the adjustment changing at least one of the set of algorithm characteristic values for a predictive analytic algorithm. Deployment of the predictive analytic algorithm may then be initiated in an enterprise operations workflow and at least one result may be generated. The deployed predictive analytic algorithm may then monitor the result and generate an alert signal when the result exceeds a boundary condition.

Abstract: A data store may contain electronic records representing a plurality of potential associations and, for each potential association, an electronic record identifier and a set of attribute values. An automated electronic record classification computer may classify electronic records from the data store into sub-sets of related records. An automated scoring analysis computer may retrieve, for each electronic record in a classified sub-set, the set of attribute values and calculate at least one attribute analysis score (based on attribute values of other electronic records in the same sub-set). A back-end application computer server may retrieve attribute values along with an attribute analysis score associated with an electronic record of interest and automatically retrieve third-party data. Data associated with an interactive user interface display, including the at least one attribute analysis score and the third-party data, may then be via a distributed communication network.

Abstract: Methods, methods, apparatus, computer program code and means to evaluate performance via a distributed communication network are provided. In some embodiments, a computer store may contain data for a plurality of source channels, including, for each source channel, historic interaction information. A back-end application server may receive from a remote administrator computer a selected source channel identifier and automatically identify historic interaction information in the computer store associated with the selected source channel identifier. The back-end application server may then evaluate the identified historic interaction information and associated benchmark indications to generate a set of performance metric scores for a selected source channel matching the selected source channel identifier and aggregate the set of performance metric scores to calculate an overall aggregated performance score for the selected source channel.