Data Accuracy: Assessing Faithfulness and Error Detection

This lecture covers the assessment of data accuracy, focusing on the faithfulness of records within a dataset, error detection taxonomy including outliers and duplicates, handling outliers by deletion or default setting, correlations within records, functional dependencies, FD violation detection, FD discovery, Tane algorithm for FD discovery, conditional functional dependencies, matching dependencies, denial constraints, detecting denial constraint violations, data repairing techniques, and the minimality of repairs principle in data repairing automation.