How does Saviynt manage 'Identity Data Quality'?

Saviynt manages 'Identity Data Quality' primarily through built-in validation and cleansing processes for identity-related data. This approach ensures that the data entered into the system adheres to specific standards and formats, reducing the likelihood of errors and inconsistencies. The built-in mechanisms can automatically check for duplicate entries, validate email addresses, and ensure that required fields are filled in correctly, thereby enhancing the overall integrity of the identity data.

These validation and cleansing processes are critical because high-quality identity data underpins effective identity governance and management. Organizations need to trust that the data they rely on for decision-making, compliance, and security is accurate and up-to-date.

In contrast, relying on manual data entry could introduce more errors due to human factors, and external audits and assessments would not address ongoing data quality issues in real-time. Limiting user inputs to standard fields could help somewhat, but it does not provide the dynamic cleansing and validation processes that are crucial for maintaining high data quality over time.