Assess construction data quality using completeness, accuracy, consistency, timeliness, and validity metrics. Automated validation with regex patterns, thres...
- Added comprehensive data quality assessment covering completeness, accuracy, consistency, timeliness, and validity for construction datasets. - Introduced automated validation using regex patterns, rule-based thresholds, and column checks. - Included programmatic usage examples and quick start guide in Python. - Enhanced reporting with per-metric results, threshold checks, and detailed issue logging. - Documentation now references the DDC methodology and main quality standards for construction data.