How are Data Quality Helper’s validation rules different from what is offered out of the box by Salesforce?
Data Quality Helper validation rules are different in a couple ways:
- Standard Salesforce validation rules are known as “hard” validation rules. This means the user may not save a record until a validation warning is not encountered. With Data Quality Helper, the Admin may configure a “hard” or a “soft” validation rule. Soft validation rules allow users to continue with the save after the warning message is displayed, allowing them to decide they have a valid reason to do so.
- Data Quality Helper validation rules also have highly customizable warning message formatting. This allows the Admin to change font style, font size, font color, and background color, as well as include merge field values in the warnings displayed to a user. Unfortunately, standard Salesforce validation rule warning formatting may not be changed and do not allow merge field values in their warnings.
See the Data Quality Helper Overview Page for more information.
How are Data Quality Helper’s duplicate rules different from what is offered out of the box by Salesforce?
Data Quality Helper duplicate rules are different in a few ways:
- Data Quality Helper duplicate rules may be created for any object type, while Salesforce duplicate rules may not be created on every standard object type.
- Data Quality Helper duplicate rules also allow Admins to define and adjust how similar a field value has to be for a record to be flagged as a duplicate.
- Users are given the chance to view and compare two different fields when checking if their values truly are the same.
- Users also are given more control over what field values are used when records are merged.
Does Data Quality Helper allow users to save records even if a validation rule or duplicate records are detected for a record?
Yes, if the Admin determines it is allowed when configuring the rule.
Why is Data Quality Helper better than default Salesforce functionality?
Data Quality Helper offers more customization, flexibility, and better usability. It also provides tools that assist with cleanup for historic records. Simply put, this solution meets the needs for any type of organization.
Can users prevent warning messages from displaying in the future if they confirm the data they have entered for the record is valid?
Yes. Admins may decide which rules can be ignored. If the Admin decides a rule is very important and should not be ignored, they may do that as well.
Does Data Quality Helper have a free version?
Yes. The free version allows for the configuration of two validation rules and one duplicate rule. The premium version allows for unlimited rules of either type.
Does a user have to create/edit a record in order to see warning messages?
No. Data Quality Helper has two Lightning Web Components that may be used to display warning messages without requiring a user to edit/create a record. One component may be added to the record detail page, showing data quality issues with a record being viewed. The other component may be added to the home page, displaying either all or only owned records with data quality issues.
Can Data Quality Helper create validation and duplicate rules on any object type?
Yes. There are no limitations—rules can be created for any type of object.
What is your release process?
See Future Release Process.
Does Data Quality Helper help me find data quality issues for records that were created prior to the configuration of a rule?
Yes. After a rule is configured you may:
- go back to the Data Quality Helper home page
- select the option for the type of rule that was just created
- click the dropdown arrow next to the rule that was just created
- click the Log Validation Issues menu item
Once all issues are logged you may view the home page Lightning Web Component to see all records with data quality issues.
Why are soft validation rules valuable? Why should we allow users to bypass validation rules?
There are many reasons why an organization would like to allow its users to bypass defined validation rules.
- In most situations, the data input on a record should follow the standards set in place by an organization. However, sometimes those standards cannot be achieved. For example let’s say an organization prefers to reach out to contacts via a phone number populated on the contact record. Sometimes that phone number is not correct and other times that phone number is not provided or available. Would you prefer to prevent that contact from being created, or would you still want that contact to be created with other forms of contact such as email? We’ve found that in most situations organizations still want those contacts to be created.
- Soft validation rules may be put in place to inform users of a cascading effect before or after a save of a record. Let’s use a time-off request as an example. Say a user has 10 hours remaining in their balance of time off remaining for the year. If that user logs a time off request for 20 hours, wouldn’t it be important to inform that user that they are requesting more hours off than what is remaining in their balance and also to inform them that if they continue to request the time off they will have some unpaid time off?
- Sometimes data is only available at a later date. Let’s say your organization is working on a project for one of your customers. In most cases, key information such as the start date is known right away, but that is not the case 100% of the time. It’s important for your organization to prepare for a project regardless of when the project is set to begin. So having all the known project information in Salesforce is important even if that project is missing key information such as the start date. It’s simple to find those project records without start dates if a start date validation rule is defined, so the user can easily populate that information once it is known.
