Comprehensive Data Quality and Validation Framework

Create an enterprise-grade data quality assessment and validation framework in Python. Develop a system that performs multi-dimensional data quality checks, including statistical distribution analysis, anomaly detection, schema validation, and cross-source reconciliation. Implement automated reporting, with detailed metrics on data completeness, consistency, accuracy, and timeliness. Include machine learning-based anomaly detection and a flexible, configurable validation pipeline that can be integrated into existing data infrastructure.