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Validation rules verify that data entered by users in records meets the standards you specify before they can save it. Validation rules can also include error messages to display to users when they enter invalid values based on specified criteria. Using these rules effectively contributes to quality data. For example, you can ensure that all phone number fields contain a specified format or that discounts applied to certain products never exceed a defined percentage.

You can create validation rules for objects, fields, campaign members, or case milestones. In these steps, we create a validation rule that fires when a user tries to save an account with an account number of incorrect length.

The AND function returns a value of "True" if all values in the formula are true, and a value of "False" if one or more values are false. The NOT function determines if the inverse of an expression is true. In the example, the validation rule determines if an account number is both not blank and not a number. A value of "True" indicates that the data entered by the user contains an invalid value. That is, if the user enters a non-numeric value for an account number, the validation rule returns a response of "True" and sends an error message.

The YEAR function returns the four-digit year of a given date. That is, if the user enters a date that is not in the current year, the validation rule returns a response of "True" and sends an error message. In the example, if the user enters a website URL with an extension that is not equal to is either greater than or less than all six of the valid extensions, the validation rule returns a response of "True" and sends an error message.

If the user enters a website URL with an extension that is identical to is not greater than or less than one of the valid extensions, the validation rule returns a response of "False" and does not send an error message, because the data the user entered is valid. This rule rejects the specified field as bad data and writes the record to the bad data file. This rule is designed to be used in conditional statements as one action to take if a field value fails its validation.

The syntax for reject is:. This sample checks whether the SSN field is null. If the SSN field is null, the record is rejected and written to the bad data file. This rule returns the specified field as good data. This rule is designed to be used in conditional statements as the action to take if a field value passes its validation. The syntax for return is:.

For a sample of the return rule, see the sample for reject. This rule validates the specified fields against the length defined for those fields in object. You can specify whether to reject records that exceed the defined length or to truncate the field value to the defined length. The syntax for validateDBField is:. The parameters for validateDBField are a list of fields and the action to take for each field.

The field elements take the following parameters:. The following sample checks the length of the social security number and last name in each record. If the social security number is too long, the record is rejected and written to the bad data file. If the last name is too long, it is truncated. Data Validation Rules You can define rules to validate certain fields against specific values, a range of values, patterns, and length. Example 4 Sample dataLength Validation Rule This sample defines a rule to check for records containing first names that are 30 or more characters and containing last names that are shorter than two characters.

Example 6 Sample matchFromFile Rule This sample defines a rule that validates State fields against a list of valid state abbreviations contained in the file State. Example 8 Sample range Rule This sample validates United States postal codes to be sure they fall within a valid range. Example 10 Sample return Rule For a sample of the return rule, see the sample for reject. You can only define validation rules for persistable entities as they are designed to ensure database integrity.

Therefore, validation rules are disabled for non-persistable entities. You can add and edit validation rules for an entity from the entity dialog box. Attribute specifies the attribute to which the validation rule applies. The validation rules apply to attributes of the entity and, if it has a generalization, the attributes of its generalization. Error message defines the message that is displayed to the end-user when the attribute value does not satisfy the condition defined by the validation rule.

Date values should be entered in ISO format, for example Validation rules can be ordered in Studio Pro. The order of the rules determines the order they are applied. If multiple rules are violated, all their error messages will be recorded in the defined order and shown in the page.

Although the order can be set for all the validation rules in the entity, only the order per attribute will have an impact as all validation rules are executed for all attributes. The uniqueness validations do not follow the defined order. This validation requires a database query and is executed only when the complete object satisfies all the other validation rules.

The uniqueness validation constraint is handled by the database. This enables stateless clustering, a higher number of concurrent users, and applications with a high transaction rate to be handled efficiently.

There are some things you need to consider when applying a uniqueness constraint, especially if you have existing data in the entities to which you are adding the constraint. The uniqueness constraint will take into account the way that the underlying database deals with case sensitivity. For a full discussion of this, see Case-Sensitive Database Behavior.