Adjustment of the ruleset check scope
By default, a ruleset check is based on a sample of 1,000,000 rows from the dataset. This ensures performance efficiency, especially for very large tables.
However, you can customize the scope of the check — by increasing or decreasing the sample size, by applying filters to focus the validation on specific parts of the data, or by choosing which columns are included in the check.
How to adjust the scope
Go to the table
Click “More” → “Manage ruleset” →"Ruleset check scope"
In the scope screen, you can:
Enter a specific number of rows
Tick “No row limit” to skip samplingOptionally apply a filter to include only specific records
Choose which columns are included — untick “Always include all columns” to select them individually
Adjust sample size or filter down to relevant segments.
Showing and hiding columns
By default, every column of the table is part of the check (“Always include all columns”). Untick this option to select the included columns yourself. Hidden columns are not considered in rule execution, samples, profiling, or downloads.
If a column you want to hide is already referenced by existing rules, the platform detects the conflict and asks for confirmation before those rules are deleted.
The column scope applies to the entire ruleset — every user sees the same restricted scope.
Use case examples
Use 100,000 rows to get fast validation during development
Tick “No row limit” for critical production tables
Add a filter to validate only rows from the last 30 days
Hide sensitive or irrelevant columns (e.g., personal data) so they never show up in checks, samples, or profiling
Notes
Smaller samples reduce computing time but may miss edge cases
Full dataset checks may increase cost and processing time
Filters help validate targeted business scenarios
Learn more: Setting up a Table Check, Sampling Behavior, Filters for Data Quality Checks
Hidden columns are excluded for all users of the ruleset — in rule execution, samples, profiling, and downloads