Knowledge Article

Advanced Analytics Milestone

Author

  • ryan_cutter

    SailPoint

Ensuring the accuracy and integrity of identity and access data is crucial for the success of the Advanced Analytics milestone. By thoroughly verifying and correcting this data within the Identity Security Cloud or IdentityIQ platform, organizations can enhance governance, streamline administrative processes, and prevent potential security gaps. This document provides guidelines to identify and rectify common data issues, laying a solid foundation for advanced analytics capabilities.

 

1

Verify and correct identity and access data

Resources:

Identity Security Cloud

IdentityIQ

Advice:

Make to sure to validate and verify that correct identity and access data models are represented within the platform. Review the data with the various application/source owners so that you know you are working with good, clean and mostly accurate data. By using the standard out-of-box reports and/or search query capabilities, you can mine the data and help application/source owners with their clean up efforts. Do not forget to adjust configurations and other settings as needed.

The following should be verified/corrected:

  • Uncorrelated Accounts
  • Identities Without Managers
  • Data Quality and Accuracy
  • Data Transformations
  • Entitlement Names and Descriptions
  • Errors and Exceptions

Pitfalls:

  • Uncorrelated accounts can create governance blind spots.
  • Identities without managers can affect governance and administrative processes, such as manager certification campaigns and approvals.
  • Poor data quality can hinder governance and administrative functions, including identification, correlation, classification, and automated access assignments.
  • Inadequate or unclear entitlement names and descriptions can confuse end-users.
  • Failing to address errors and exceptions early can delay project timelines and affect future efforts.