Intelligent Data Quality Framework Powered by AI for Reliable, Informed Business Decisions

Abstract

This research looks into developing a data quality framework relying on AI to ensure more accurate decisions for financial companies, supply chain management, and healthcare providers. When data accumulates and comprehensive validation isn't achievable, organizations struggle with inconsistencies, redundant records, and missing information. Using natural language processing, anomaly detection, and machine learning, the proposed framework automatically cleans data, improves accuracy, and maintains consistency in various data systems. This research looks at workflows of AI and frameworks that are being put together to propose practical and scalable methods for better data use, and compliance within various industries.