Overcoming Data Quality Challenges in IAM

Many organizations experience the hidden costs of low-quality user data, which makes automating routine Identity Management and provisioning tasks difficult and drives unnecessary operational and support costs. During this webinar, we will walk through mini-case studies that showcase common problems, identify root causes, and provide recommendations to improve data quality and drive new results from your existing IAM systems. We will discuss:

• The impact of poor data quality and common causes
• The importance of developing a Data Map to determine attribute flow across systems to mitigate problems
• Prioritizing user attributes and defining a minimum data set
• Understanding the role that process plays in either supporting or degrading data quality
• Having systems trap for incorrect or incomplete user data automatically
• Linking data remediation activities to the Governance model within your organization