Validator
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Supported formats: .csv,.xlsx,.xls,.xlsm,.xlsb,.tsv
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About Validator
Check if data meets specific logical rules.
You define one or more rules per column, numeric range, non-empty, regex pattern match, or membership in an allowed list, and the tool evaluates every row against them, flagging exactly which rule each failing row broke. Rather than silently rejecting bad data, it produces a per-row pass/fail report so you can decide how to handle exceptions before the file moves downstream.
Category: Transformation & LogicCommon Use Cases
- Verifying an "age" column only contains numbers between 0 and 120 before importing into a database
- Checking that every row in an "email" column matches a valid email pattern before a mail merge
- Confirming a "status" column only contains values from an approved list before publishing a report
Key Features
- Configurable rules per column: range, non-empty, pattern match, allowed values
- Per-row pass/fail flagging with the specific rule that failed
- Summary report of how many rows failed each rule
Run Data Health first for a general overview of quality issues across the whole file, then define specific rules here to enforce business logic; use Filtering afterward to isolate and remove the rows that failed validation.
Frequently Asked Questions
Logical rules you define, for example that a column must be numeric, non-empty, or fall within a specific range.
The tool flags which rows don't meet your rules so you can review or fix them.
A gatekeeping step for teams that need to enforce data quality rules before a file is trusted downstream.
Read the related guide →