Abstract: In an illustrative embodiment, systems and methods for generating data metrics and relationship analysis from an organization's electronic communications archives include pre-processing the electronic communications into a consistent, workable format, including filtering the data to remove irrelevant messages. Machine learning models may be applied to support automatic identification of relevant message content for data analytics. The systems and methods may link the electronic communications with transaction records of a transactional platform and analyze the communications traffic in view of transactional patterns and outcomes. Communications between parties may be analyzed to identify timings and patterns, plus correlations between electronic communication patterns and business outcomes.

Abstract: In an illustrative embodiment, systems and methods for performing cascading matching of data records from disparate data sources comprise identifying matches using at least one uniquely identifying data field and at least one additional data field shared by a first data set and a second data set. Potential matches may be resolved through calculating differences between one or more shared data fields of a matched data record of the first data set and both a first matched record and a second matched record of the second data set, and determining a best match through analyzing the calculated differences. Unmatched records may be iteratively matched using a different uniquely identifying data field and/or different at least one additional data field(s).

Abstract: In an illustrative embodiment, systems and methods for generating data metrics and relationship analysis from an organization's electronic communications archives include pre-processing the electronic communications into a consistent, workable format, including filtering the data to remove irrelevant messages. Machine learning models may be applied to support automatic identification of relevant message content for data analytics. The systems and methods may link the electronic communications with transaction records of a transactional platform and analyze the communications traffic in view of transactional patterns and outcomes. Communications between parties may be analyzed to identify timings and patterns, plus correlations between electronic communication patterns and business outcomes.

Abstract: In an illustrative embodiment, systems and methods for performing cascading matching of data records from disparate data sources comprise identifying matches using at least one uniquely identifying data field and at least one additional data field shared by a first data set and a second data set. Potential matches may be resolved through calculating differences between one or more shared data fields of a matched data record of the first data set and both a first matched record and a second matched record of the second data set, and determining a best match through analyzing the calculated differences. Unmatched records may be iteratively matched using a different uniquely identifying data field and/or different at least one additional data field(s).

Abstract: In an illustrative embodiment, systems and methods for performing cascading matching of data records from disparate data sources comprise identifying matches using at least one uniquely identifying data field and at least one additional data field shared by a first data set and a second data set. Potential matches may be resolved through calculating differences between one or more shared data fields of a matched data record of the first data set and both a first matched record and a second matched record of the second data set, and determining a best match through analyzing the calculated differences. Unmatched records may be iteratively matched using a different uniquely identifying data field and/or different at least one additional data field(s).

Abstract: In an illustrative embodiment, systems and methods for generating data metrics and relationship analysis from an organization's electronic communications archives include pre-processing the electronic communications into a consistent, workable format, including filtering the data to remove irrelevant messages. Machine learning models may be applied to support automatic identification of relevant message content for data analytics. The systems and methods may link the electronic communications with transaction records of a transactional platform and analyze the communications traffic in view of transactional patterns and outcomes. Communications between parties may be analyzed to identify timings and patterns, plus correlations between electronic communication patterns and business outcomes.