Fast, scalable validation with xBRL-CSV table constraints
XBRL International’s Best Practices Board has published new draft guidance on using xBRL-CSV Table Constraints to improve validation efficiency for large, granular datasets. This approach embeds simple validation rules directly into the xBRL-CSV metadata, enabling early error detection as data is initially processed.
Table Constraints offer a practical way to address performance limitations when dealing with millions of rows. They support streaming validation, reduce memory use, and can catch structural issues quickly, saving time and resources before more complex business logic checks are applied.
This guidance is especially useful for taxonomy authors and data collectors looking to streamline validation without sacrificing rigour. Table Constraints complements, rather than replaces, existing Formula Rules, and provides a clear strategy for layering validation for better performance and clarity.
The draft is open for review, and feedback is warmly encouraged.
