Data Validation
Turn data quality rules into visible errors and warnings so you catch problems before exporting or uploading your spreadsheet.
Overview
SheetTool's validation engine lets you define rules for individual columns and immediately see which cells pass or fail. Rules include required fields, email format, numeric checks with min/max bounds, text length constraints, regex pattern matching, and uniqueness enforcement. Each rule can be set to error severity (blocking, shown in red) or warning severity (advisory, shown in yellow). Validation results appear as highlights directly in the grid so you can fix issues in place before exporting.
Syntax & Reference
- Required
- Ensures the column has no empty cells. Use for fields that must be present in every row, like SKU, email, or product title.
- Validates that cell values match standard email format (user@domain.tld). Catches missing @, invalid domains, and formatting errors.
- Number
- Verifies that values are numeric. Supports optional min and max bounds to enforce ranges like price > 0 or quantity <= 10000.
- Length
- Enforces minimum and maximum text length. Useful for fields with character limits like product titles, descriptions, or codes.
- Regex
- Validates values against a custom regular expression pattern. Use for structured formats like phone numbers, postal codes, or custom IDs.
- Unique
- Ensures no duplicate values exist in the column. Essential for key columns like order IDs, customer IDs, or usernames.
- Severity: Error vs. Warning
- Errors are blocking issues shown in red — things that would break an import. Warnings are advisory issues shown in yellow — items that need human review but may be acceptable.
Examples
Product import pre-check
Set SKU, Price, and Title as required fields with error severity. Add a number rule on Price with min=0.01. Run validation to see all issues before uploading to your ecommerce platform.
CRM lead list cleanup
Add an email validation rule on the Email column and a required rule on Company Name. Set email issues as errors and company name as warnings to prioritize fixes.
Enforce unique identifiers
Apply a uniqueness rule to Order ID or Customer ID to catch duplicate entries that could cause conflicts during import.
Custom format validation
Use a regex rule with the pattern ^[A-Z]{2}-\d{4}$ to validate that product codes follow a specific format like AB-1234.
Tips & Best Practices
- Use error severity for rules that would break an import and warning severity for items that need human review.
- Run validation after cleanup and type casting to reduce false positives from formatting inconsistencies.
- Stack multiple rules on the same column — for example, require a field AND validate its format.
- Fix validation errors from top to bottom: required fields first, then format issues, then uniqueness.
Frequently Asked Questions
Can I validate multiple columns at once?+
Yes. You can add validation rules to as many columns as needed. Each column can have multiple rules (e.g., required + email format). All rules are checked simultaneously and results are shown in the grid.
What happens when validation finds errors?+
Cells that fail validation are highlighted in the grid — red for errors, yellow for warnings. You can see a count of issues and navigate between them. The data is not modified; validation only highlights problems for you to fix.
Do validation rules persist across sessions?+
Validation rules are saved as part of your auto-saved session data. When you reload the page, your rules and their results are restored.
Can I export only the rows that pass validation?+
You can combine validation with filtering to show only rows without errors, then export the filtered view. This gives you a clean export while keeping the full dataset in the editor.