Predictive Data Quality Engineering: Machine Learning Approaches For Enterprise-Scale Anomaly Detection And Autonomous Remediation

Abstract

Data quality remains one of the most persistent and consequential challenges facing modern banking dataplatforms, where billions of records pass through intricate pipeline architectures every day to sustain regulatory reporting, risk management, and customer engagement operations