Principle:Sdv dev SDV Diagnostic Reporting
| Knowledge Sources | |
|---|---|
| Domains | Data_Quality, Diagnostics |
| Last Updated | 2026-02-14 00:00 GMT |
Overview
A diagnostic evaluation framework that checks synthetic data for structural validity, data coverage, and boundary adherence.
Description
Diagnostic reporting focuses on basic data quality checks rather than statistical fidelity. It verifies that synthetic data has valid structure (correct types, no impossible values), adequate coverage (all categories represented, numerical ranges covered), and boundary adherence (values within expected ranges). Unlike quality evaluation which measures distributional similarity, diagnostics identify fundamental issues with the generated data.
Usage
Use diagnostic reporting alongside quality evaluation to catch structural issues that quality scores might not reveal.
Theoretical Basis
The diagnostic report evaluates three property categories:
- Data Validity: Column types and value ranges are correct
- Data Structure: Relationships and keys are valid
- Data Coverage: All categories and value ranges are represented
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