Date

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The Date check ensures that the string value in the column conforms to specified date format and is a valid date. If the value does not conform, the check fails. This enables users to enforce validity-based data quality rules without writing any expressions.

Steps

1. Navigate to the Checks tab of the Validation Rule.
2. Click edit ✏️ button to rename the Check which is by default Chk_[Sequential_Number].
3. Select Add, then choose Date.
4. Search and select the column to perform the Date check on.
5. Choose a Date pattern:

• Custom Pattern – Allows the user to enter a custom date pattern in a text field.
• Standard Pattern – Select from a predefined list.
  • Available Date format:
    • dd-MM-yy
    • dd-MM-yyyy
    • dd-MMM-yy
    • dd-MMM-yyyy
    • MM-dd-yy
    • MM-dd-yyyy
    • dd/MMM/yy
    • dd/MMM/yyyy
    • MM/dd/yy
    • MM/dd/yyyy
    • yyyyy.MMMMM.dd GGG hh:mm aaa
    • EEE, d MMM yyy HH:mm:ss Zipcode
    • yyMMddHHmmssZ
    • yyyy-MM-dd'T'HH:mm:ss.SSSZ

Property	Description
Ignore Nulls	If enabled, the engine will not apply the check, resulting in a success state.

7. Use the test feature to validate the check logic without running the full rule. Enter sample input values in the text fields and click the Play button to view the output.
8. Optionally, provide a Check Description to explain the purpose and business logic.
9. Optionally, tag a Data Quality Dimension to the check.
10. Finalize the check by selecting one of the following options:

• Cancel – Discard the check.
• Save – Save the check and close the configuration window.
• Save and Next – Save the current check and proceed to create a new one.

Output

• true – When the value matches the date pattern.
• false – When the value does not match the date pattern.

Example:
Rule: BirthDate: Pattern: dd-MM-yyyy
Input: 10-10-1986 → Output: true
Input: 01-13-2000 → Output: flase

note

This check is currently supported only for columns with String datatype.
A single check can be applied to only one attribute. To validate multiple attributes, create separate Datatype checks for each.

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