What is Field Validation?
Field Validation is a powerful tool that allows you to define and enforce specific rules for data entry across Business Central. It acts as a gatekeeper, ensuring that the information entered into any
field meets your company's standards for completeness,
accuracy, and format. Unlike security tools that control who can edit data, Field Validation controls what data is considered valid.
The Power of Conditional Logic
One of the most powerful features of Field Validation is its use of conditional logic. You don't want to bombard users with validation errors when they are just
creating a new draft record. The rules should only apply when it matters.
With Field Validation, you can set conditions that trigger your
rules. A common and highly effective example is to apply a set of rigorous checks only when a user attempts to change a record's status from "Blocked" to "Active."
Scenario: Imagine a user unblocking a customer. You can configure the app to check, at that exact moment, if:
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A credit limit has been set.
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A valid delivery address is on file.
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A primary contact person has been assigned.
If any of these rules fail, the action is stopped, preventing an incomplete customer record from entering your active processes.
Key Validation Rules to Transform Your Data Quality
Field Validation offers a wide array of rule types to tackle any data integrity challenge. Here are a few key examples:
1. Required Fields & Specific Values The most basic rule, but essential. Ensure critical fields are never left blank. You can also enforce that a field must contain a specific value (e.g., Country/Region Code must be 'NL' for domestic orders).
2. Format Enforcement with Regular Expressions (RegEx) Ensure data consistency by enforcing a specific format. This is perfect for:
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Postal Codes: Require a format like 1234 AB.
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VAT Registration Numbers: Enforce the correct country-specific structure.
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Email Addresses: A simple check to ensure the entry includes an '@' symbol and a domain.
3. Relational Data Checks This is where Field Validation truly shines,
allowing you to validate data based on related records.
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Related Number of Records: You can require that a related record exists. For example: "A Customer cannot be unblocked unless at least one Bank Account record has been created for them."
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Related Field Value: You can compare a field's value to a field in another table. For example: "The Salesperson Code on a Sales Order must match the Salesperson Code assigned to the Customer."
4. Error vs. Warning: Flexibility in Enforcement Not every rule break is a critical failure. Field Validation gives you two options:
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Error: This is a hard stop. The user cannot proceed until the data is corrected. The entire change is rolled back.
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Warning: This notifies the user of an issue but allows them to proceed. This is incredibly powerful when combined with a Follow-up Action. For instance, you could allow a salesperson to enter an
unusually high discount, but the system will show a warning and automatically change the order's status to"
Needs Manager Approval," preventing it from being posted.
Bringing It All Together: A Practical Example
Let's say you want to improve the process for creating new vendors. You can create a single Field Validation setup that:
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Condition: Triggers only when the Blocked field is set to empty (i.e., the vendor is being activated).
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Rules:
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Required: The VAT Registration No. field must not be empty.
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RegEx: The VAT Registration No. must match the valid format for the vendor's country.
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Related Records: The vendor must have at least one Vendor Bank Account set up.
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Warning: If the Payment Terms Code is for immediate payment, show a warning to the user to double-check, but allow it.
Proactive Control Over Your Data
By implementing Field Validation, you shift from reactive data cleanup to proactive data governance. You empower your
users to get it right the first time, leading to:
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Improved Data Accuracy: Fewer errors and inconsistencies in your master data.
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Smoother Business Processes: Reduced delays caused by incomplete or incorrect information.
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More Reliable Reporting: Confidence that your reports and analytics are based on solid,
trustworthy data.
Stop chasing data errors and start preventing them. Improve your data consistency in Business Central and build a more robust foundation for your business operations.
