Abstract: Systems and methods for obfuscating sensitive data by aggregating the data based on data attributes are provided. Each sensitive data record contains at least one sensitive attribute. A data protection system generates a data transformation model based on the sensitive data records and transforms the sensitive data records using the data transformation model. The data protection system further compresses the sensitive database by grouping the sensitive data records into aggregation segments based on the transformed sensitive data records. The data protection system generates aggregated data by calculating statistics for the at least one sensitive attribute contained in the sensitive data records in each of the aggregation segments. The aggregated data can be made accessible by client computing devices that are unauthorized to access the sensitive data records.

Abstract: Attribute data structures can be updated to indicate joint relationships among attributes and predictive outputs in training data that can be used for training automated modeling system. A data structure that stores training data for training an automated modeling algorithm can be accessed. The training data can include first data for a first attribute and second data for a second attribute. The data structure can be modified to include a derived attribute that indicates a joint relationship among the first attribute, the second attribute, and a predictive output variable. The automated modeling algorithm can be trained with the first attribute, the second attribute, and the derived attribute.

Abstract: Attribute data structures can be updated to indicate joint relationships among attributes and predictive outputs in training data that can be used for training automated modeling system. A data structure that stores training data for training an automated modeling algorithm can be accessed. The training data can include first data for a first attribute and second data for a second attribute. The data structure can be modified to include a derived attribute that indicates a joint relationship among the first attribute, the second attribute, and a predictive output variable. The automated modeling algorithm can be trained with the first attribute, the second attribute, and the derived attribute.