Data validation
A View brings together the fields and controls needed to represent required information. Data validity is an essential consideration in this design, because accurate, well‑formed data supports reliable system behavior and consistent processing outcomes.
Data validation requirements
Valid user‑entered data supports smooth, end‑to‑end workflow execution by reducing errors and interruptions.
The following table outlines examples of data validation requirements:
| Data requirements | Examples |
|---|---|
|
Use the appropriate Field Type. |
The Total purchase units value is a numeric value. |
|
Restrict input to valid values. |
The Loan type value comes from a predefined set of options. |
|
Ensure that data aligns with business logic. |
The Date of birth value represents a date in the past. |
Data validation prevents processing errors by ensuring that entered values meet business expectations. In many cases, controls or Field Types are sufficient to constrain data to valid formats or structures. When these mechanisms cannot fully capture business intent, validation logic is used to evaluate field values against defined conditions.
For example, a Date only Field Type ensures that a value represents a valid date, regardless of format. However, it does not determine whether a Start date is appropriate. Additional validation logic closes this gap by evaluating whether the date aligns with the business requirement, such as ensuring it occurs in the past.
Data validation with controls
Controls are a common mechanism for supporting data validity. By shaping how values are selected or entered, controls help constrain input to acceptable formats, ranges, or options, reducing the likelihood of invalid data.
Control types
Different control types support data validation in different ways by influencing how users provide input. Appropriate control types align user input with business expectations. The following table provides example use cases for different control types:
| Control type | How the control supports validation | Use case |
|---|---|---|
| Date Time |
Represents input as a structured date value, ensuring consistency in how date information is captured. |
A date value includes a day, month, and year. |
| Radio buttons |
Limits input to a small, predefined set of options and ensures that only one value is selected. |
One of three possible loan types is selected, with all options visible. |
| Dropdown |
Constrains input to a defined list of values while displaying options only when needed. |
One office chair type is selected from a list without showing all options on the form. |
| Autocomplete |
Narrows available options as text is entered, making it easier to select a valid value from a large set. |
A country is selected by typing part of the country name. |
| Checkbox |
Captures a binary choice, representing a value as either selected or not selected. |
An option to purchase additional travel insurance is selected or left unselected. |
Required fields
Required fields ensure that essential data is present before a form can be submitted. An empty required field results in an error, while a populated field allows submission to proceed. For example, a Date of birth field requires a value to be provided in order to be considered complete.
Business logic data validation
Simple validation logic supports data quality by evaluating field values against defined criteria. When a value falls outside acceptable limits, an error is communicated and Case progress is paused until valid data is provided. This approach helps ensure that only acceptable values are carried forward during Case processing.
Validation logic ensures that data entered by users meets defined expectations before a Case can continue. For example, a condition can identify invalid data by flagging values that are less than or equal to 100 when a value greater than 100 is required. Clear error messages communicate why the input is invalid and guide users on how to correct it. At runtime, the entered data is evaluated against these conditions, and if it does not meet the requirement, an error is displayed and the Case is prevented from progressing until the issue is resolved.
The following image shows how a validation condition defines invalid values and sets an error message:
The following image shows how an error is displayed when the entered value does not meet the condition:
Business logic validations are used in the Case Lifecycle to check field values against specific business requirements. These validations are implemented as Validate Rules, which are separate from the fields that capture data, so the validation is not automatically repeated when the field is reused later.
The same field can appear on multiple forms with different validation rules applied in each context. For example, a Start date field may require a past date on a Job History form and a future date on a New Hire form. Applying different business logic validations ensures that users enter values that match each business scenario.
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Validation on a form
Business logic validation on a form addresses situations where user input cannot be fully predicted or constrained. Validation evaluates submitted data against defined conditions and identifies values that do not meet business expectations. When invalid data is detected, an error is presented and the Case does not progress until acceptable data is provided. This type of validation is most effective when users can immediately correct the issue within the same form.
For example, a Date of birth field can accept a valid date value based on its Field Type and control, but this does not indicate whether the date itself is appropriate. Business logic validation distinguishes acceptable values by identifying dates that occur in the future as invalid. Once the value reflects a date in the past, it satisfies the business requirement and the Case can proceed.
The following image shows how validation is associated with a Step for the Date of birth field:
The following image shows how invalid values are identified and prevented during data entry:
Validation on a Stage
Business logic validation ensures that a Case progresses only when required data meets defined expectations. These checks are applied at key points in the Case Lifecycle, preventing the Case from advancing when conditions are not satisfied.
Stage entry validations reinforce this by evaluating data before a Case enters a new Stage. If required conditions are not met, the transition is blocked, ensuring that each Stage begins with complete and valid data aligned with business rules.
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