Validate data integrity and check for errors with comprehensive validation rules
Upload data and define validation rules to check data quality
Drag & drop a CSV or JSON file here, or click to select
Supports CSV and JSON files for validation
Data validation is the process of checking data quality and accuracy against predefined rules and constraints. It ensures that data meets specific criteria before it's processed or stored. Data validation is crucial for maintaining data integrity, preventing errors in downstream processes, ensuring compliance with business rules, and improving overall data quality in databases and applications.
The Data Validator supports 9 types of validation rules: Required (field must not be empty), Email (valid email format), Phone (valid phone number), Number (numeric values only), Date (valid date format), URL (valid web address), Regex (custom pattern matching), Length (string length constraints), and Range (numeric value range). You can apply multiple rules to the same column for comprehensive validation.
First, upload your CSV or JSON file using the drag-and-drop area or file browser. Once uploaded, navigate to the Rules tab to create validation rules for your data columns. Select the column, choose the validation type, and configure any additional parameters like min/max values or regex patterns. Click Validate Data to run the validation and view detailed results in the Results tab.
Yes! The Regex validation type allows you to define custom regular expression patterns for validating data. This is useful for validating custom formats like product codes, license plates, postal codes, or any specific pattern your data needs to match. Simply select the Regex rule type and enter your pattern in the Pattern field.
Validation results include a comprehensive summary showing total rows, valid rows, invalid rows, and pass rate percentage. Detailed error reports list each validation failure with the row number, column name, rule type, custom error message, and the actual value that failed validation. Results are color-coded with errors in red and warnings in yellow for easy identification.
You can apply multiple validation rules to the same column. For example, you might validate that an age column is both a number and within a specific range (18-100). All rules are checked for each value, and any violations are reported. This allows for comprehensive data quality checks with layered validation logic.
Yes! You can export validation results in two ways: copy the validation report to your clipboard or download it as a text file. The report includes a summary of validation statistics, a detailed list of all errors with row and column information, and any warnings. This makes it easy to share results with team members or keep records of data quality checks.
Absolutely! All data validation is performed entirely in your browser using client-side JavaScript. No data is uploaded to servers or transmitted anywhere. Your files, validation rules, and results remain completely private and secure on your device. This makes it safe to validate sensitive or confidential data.