• Audit
• Auditing
• Data Quality
• Data Quality Issues in Process Mining
• Process Mining

Digitization has transformed the way companies work, the impact this has had is extremely high, it is no coincidence that we talk about the "era of big data" and the "new industrial revolution". In particular, the study of process mining has made great strides in recent years. To date, while quantity can be taken for granted, the importance has shifted to data quality. But there is one area that has remained (still) predominantly manual. The audit field has somehow undergone digitization without actually transforming itself, but adapting to new demands. Although the use of process mining has been extensively tested in the audit field, it is still a little-used technology. Auditors are not yet able to use this tool and often can not because of the quality of data, which to be used by process mining software be prepared by undergoing transformations by analysts, this process often makes the data questionable in the audit field. The objective of this research is to identify how the quality of the data affects the judgment of the auditors and how quality issues can be addressed to allow when the data is not used as evidence, the auditor to use the information received as support for their personal judgment.