Abstract: Methods, systems, and computer program products for detecting and correcting integration issues and errors between different computer systems are disclosed. For example, a computer-implemented method may include collecting transaction data for each one of a plurality of respective merchants where the transaction data is associated with service integration between computer systems associated with the respective merchants and one or more service provider computer systems, analyzing the transaction data across a plurality of respective issue detection models, generating for each one of the plurality of merchants action data corresponding to one or more of the respective issue detection models based on the analyzing, and providing each one of the plurality of merchants with the respective generated action data.

Abstract: Methods, systems, and computer program products for detecting and correcting integration issues and errors between different computer systems are disclosed. For example, a computer-implemented method may include collecting transaction data for each one of a plurality of respective merchants where the transaction data is associated with service integration between computer systems associated with the respective merchants and one or more service provider computer systems, analyzing the transaction data across a plurality of respective issue detection models, generating for each one of the plurality of merchants action data corresponding to one or more of the respective issue detection models based on the analyzing, and providing each one of the plurality of merchants with the respective generated action data.

Abstract: Methods, systems, and computer program products for detecting and correcting integration issues and errors between different computer systems are disclosed. For example, a computer-implemented method may include collecting transaction data for each one of a plurality of respective merchants where the transaction data is associated with service integration between computer systems associated with the respective merchants and one or more service provider computer systems, analyzing the transaction data across a plurality of respective issue detection models, generating for each one of the plurality of merchants action data corresponding to one or more of the respective issue detection models based on the analyzing, and providing each one of the plurality of merchants with the respective generated action data.

Abstract: Various systems, mediums, and methods for storing and retrieving data include a non-transitory memory and one or more hardware processors coupled to the non-transitory memory and configured to read instructions from the non-transitory memory to cause the system to perform operations. The operations include obtaining base data associated with a first entity, generating predictive data based on the base data using a predictive model, and providing the predictive data to a second entity. The predictive model includes a plurality of model parameters learned according to a supervised learning process. The base data includes access-restricted data associated with the first entity, and the predictive data does not include the access-restricted data.

Abstract: Systems, methods, and computer program products are disclosed for providing a contextual recommendation corresponding to a visualization. An example method includes ingesting a data set from or more data sources, including applying rules that transform the data set into a standardized format. The subsets of the ingested data set are assigned based on a determined variable into population coverage ranges that correspond to statistical distributions of the determined variable. Distribution analysis is performed across at least one of the population coverage ranges to identify a distribution data set corresponding to the determined variable. The distribution set is parsed to identify a context recommendation. The identified context recommendation is mapped to a tag corresponding to the determined variable, and a visualization type corresponding to the distribution data set.