Abstract: A data management system identifies data stores that store transaction datasets associated with transactions. The data stores are configured based on respective parameters, and continue to receive additional transaction data over time. The system generates scripts based on the data stores' parameters and based on a filtering scheme. The system uses the scripts to extract subsets of the transaction datasets according to the filtering scheme in real-time as the data stores continue to receive additional transaction data. The system merges the extracted subsets of the transaction datasets into an output dataset according to an output scheme, and analyzes the output dataset, all in real-time as the data stores continue to receive the additional transaction data and the system continues to merge the extracted subsets. By analyzing the output dataset, the system recognizes a pattern in the output dataset. The system outputs an alert indicative of the recognized pattern.

Abstract: A data management system identifies data stores that store transaction datasets associated with transactions. The data stores are configured based on respective parameters, and continue to receive additional transaction data over time. The system generates scripts based on the data stores' parameters and based on a filtering scheme. The system uses the scripts to extract subsets of the transaction datasets according to the filtering scheme in real-time as the data stores continue to receive additional transaction data. The system merges the extracted subsets of the transaction datasets into an output dataset according to an output scheme, and analyzes the output dataset, all in real-time as the data stores continue to receive the additional transaction data and the system continues to merge the extracted subsets. By analyzing the output dataset, the system recognizes a pattern in the output dataset. The system outputs an alert indicative of the recognized pattern.