Data Quality Analysis
Data Quality Analysis is the examination of identity and access data to detect inconsistency, incompleteness, duplication, or governance defects.
Definition
Data Quality Analysis is the practice of evaluating identity data, account data, ownership data, and access metadata to determine whether IAM decisions are being made on trustworthy information. It is essential because poor data quality directly weakens recertification, role modeling, lifecycle automation, and authorization accuracy.
The Ariovis perspective
Reliable lifecycle and access decisions depend on trusted identifiers, clearly owned sources and controlled data quality. Automation should not accelerate inconsistent data.
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