validate-drd

To validate a Data Requirements Document, you can run automated completeness and quality checks against required sections, metadata, and SLAs. This process identifies gaps and outputs a severity-ranked report with actionable fixes before engineering work begins.

DRD validation is the automated process of auditing Data Requirements Documents for completeness and quality. It checks required sections, flags vague language and missing regulatory details, and assigns severity rankings to catch gaps early.

Yes, you can check multiple DRD files at once using batch validation. This feature processes several Data Requirements Documents simultaneously, identifying missing SLAs, undefined tolerance thresholds, and incomplete regulatory subsections across the entire batch.

Yes, the requirements check supports auto-remediation by automatically fixing critical structural issues like missing sections or empty metadata. It prompts for user input on business-specific gaps before finalizing the validation report.

The best way to audit business analysis requirements is to apply an automated quality audit that flags vague language and missing SLAs. This approach outputs severity-ranked findings with actionable fix suggestions to ensure data-centric project requirements are complete.

The DRD file needs to be in Markdown format for the validation script to process it. The tool requires a Markdown file as input to parse the sections, metadata, and requirements, and outputs a severity-ranked validation report.