Data Discrepancies

In general, consider data discrepancies as qualitative problems. That means what you expect doesn't align with the data you're collecting. It is different than data quantity or identification rates. Those are normally related to integration issues which you can use the "Malfunction/Data Related Issues" Troubleshooting section to resolve. A data discrepancy example is: The industry of a company doesn't match what you'd expect such as Publishing instead of Software and Tech.