Wunderite and AMS360 both use data validation to ensure our software functions as expected. However, there are instances where the softwares validate data differently, or where legacy data exists, that may degrade the performance of the integration.

To mitigate validation issues, our team creates an AMS360 data quality report during setup. The data quality report looks at every account in AMS360 and lists specific records that may be problematic due to data validation. Ideally, the agency addresses these data quality issues before they choose to finalize the integration.

If the agency does not address the data quality report, they can expect degraded performance.

Suppose you want to share a form in Wunderite. Wunderite relies on a valid email address having been stored so that we can send an email.

Wunderite won't be able to send an email if the email is invalid. So, we only allow users to type in valid email addresses in our application.

When we integrate with another software, the other software may have a different idea of what a valid email is. Perhaps the other software allows "bob at gmail dot com". If we were to simply allow this email to be stored in Wunderite, without validating it in during the integration, then the Wunderite application would fail.

It is possible that the other software does not recognize "bot at gmail dot com" as a valid email address today, and does not let users type that in as an email field. However, for softwares that have been around for some time, perhaps the validation was newly introduced within the past few years: any email entered before the validation could be liable to be invalid, (whereas anything after the validation is valid). Thus even though validation exists, legacy data could still be invalid. If we import invalid legacy email address, the application could fail.

Wunderite flags records that will not work properly in Wunderite by generating a data quality report.

The table below highlights how Wunderite validates data coming from AMS360

To update a record in AMS360, Wunderite must pass a complete array of data for a given object. For example for a contact, we cannot simply pass the updated attribute (eg phone number) to AMS360. We must update the entire object by providing the updated data (phone number), along with the unchanged data (name, email, address, etc). The AMS360 API will validate the data (eg check that phone number is 7 or 10 digits). Thus Wunderite is prevented from updating any records in AMS360 that contain invalid legacy data.

When Wunderite encounters errors during the AMS360 setup process, we do not import the erroring records. The reasons we do not accept the erroring records is (1) app performance and (2) 2-way integration issues that get created (mainly: we don't want to overwrite data in AMS360). For this reason, we recommend updating the customer data issues found in the data quality report before finalizing your AMS360 integration.