Data Validator Node

Validate and structure data using JSON Schema.

Overview

The Data Validator node validates input data against a JSON Schema you define. It ensures data conforms to expected types, formats, and constraints before processing.

Configuration

Field	Description	Required
`Input Data`	The data to validate (supports variables)	Yes
`Root Data Type`	Object, Array, String, Number, or Boolean	Yes
`Output Variable`	Variable name to store validated data	Yes

Root Data Types

Type	Description
`Object`	Validate an object with defined properties
`Array`	Validate an array of items
`String`	Validate a string value
`Number`	Validate a numeric value
`Boolean`	Validate a boolean value

Defining Fields (Object/Array)

For Object and Array types, define the expected fields:

Click Add Field to create a new field
Set the field name
Choose the field type
Configure settings (click gear icon)

Field Types

Type	Description
`String`	Text values
`Number`	Numeric values
`Boolean`	True/false values
`Object`	Nested objects
`Array`	Nested arrays
`File`	File references

Field Settings

Click the settings icon on any field to configure:

String Settings

Min Length - Minimum character count
Max Length - Maximum character count
Pattern - Regex pattern to match
Enum - Allowed values (comma-separated)
Required - Field must be present

Number Settings

Minimum - Minimum value
Maximum - Maximum value
Enum - Allowed values (comma-separated)
Required - Field must be present

Array Settings

Min Items - Minimum array length
Max Items - Maximum array length
Item Type - Type of array items

File Settings

Allowed Extensions - Permitted file types
Max Size - Maximum file size

Array Item Types

When root type is Array, choose the item type:

Item Type	Description
`Object`	Array of objects with defined fields
`Array`	Array of arrays
`String`	Array of strings
`Number`	Array of numbers
`Boolean`	Array of booleans

Example Schema

For validating user data:

{
  "type": "object",
  "properties": {
    "name": { "type": "string", "minLength": 1 },
    "email": { "type": "string", "pattern": "^[^@]+@[^@]+$" },
    "age": { "type": "number", "minimum": 0, "maximum": 150 }
  },
  "required": ["name", "email"]
}

Using Variables

Pass data from previous nodes:

{{api_response}}
{{form_submission}}
{{parsed_json}}

Validation Output

If validation passes, the validated data is stored in your output variable. If validation fails, the workflow can handle the error in subsequent nodes.

Best Practices

Define schemas that match your expected data structure
Use required fields for critical data
Add constraints (min/max) to prevent invalid data
Test with sample data before production use