Bank of America Corporation

Charter Communications Operating, LLC

Jayanta Sengupta

Michael Bender

Scott Samuel Murray

Irina Niyazov

Sindhuja Subramani

Christopher T Walsh

Nitesh Rathod

James H Peterson

Systems, methods, devices, and non-transitory media of the various embodiments may provide for managing data quality anomalies in an enterprise system. Various embodiments may enable one or more network computing device to identify control points for monitoring data sets in the enterprise system, track data quality metrics using at least one threshold for each of the identified control points, determine whether a data quality anomaly is detected, and classify a review priority in response to determining that a data quality anomaly is detected.

System and method for identifying and handling data quality anomalies

According to some embodiments, logic executing on a processor receives a request to compare a first file and a second file. Each file comprises records, attributes, and attribute values. An attribute value is a value that a record associates with a corresponding attribute. The logic receives a mapping file indicating a key and one or more selected attributes for comparison. The logic compares each record in the first file to its corresponding record in the second file, the corresponding record determined according to the key. For records that fail to match, the logic determines which of the selected attributes are unmatched. The logic communicates a report indicating a result of comparing the first file and the second file.

Automated data validation

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Charlotte, NC, United States of America

Jayanta Sengupta