Extracting Joiner, Mover, and Leaver (JML) Data via Data Extract Feature

Which IIQ version are you inquiring about?

8.4P2

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Hi All,

We need to fetch joiner and leaver data on a real-time, monthly, or weekly basis, along with identity information such as first name, last name, email, and AD samAccountName, using the Data Extract feature. To achieve this, we are attempting to retrieve the data via the ProvisioningTransaction object class. However, we need to apply a filter where operation = create and application = Active Directory, but we have not found a way to implement such a filter in the YAML extract configuration.

  1. Does anyone have an idea on how we can apply multiple filters—such as AND, OR, greater than, and less than—within the filterString of the Extract YAML configuration.
  2. Please let us know if there is any other object class—besides ProvisioningTransaction—that can provide joiner, mover, and leaver (JML) data along with identity information.

Note: We are not looking to fetch JML data from a report, as we already have reporting in place. Our requirement is specifically to extract this data using the Data Extract feature.

If anyone has implemented a similar solution and can share details or examples, it would be greatly appreciated.

Regards,

Prashansa

Hey Prashansa,

Problem:
To make sure I understand the issue correctly: your team is trying to extract (JML) data from SailPoint IdentityIQ using the Data Extract feature. You are using the ProvisioningTransaction object class and want to filter records where operation = create and application = Active Directory.

However, you’re facing difficulty using multiple filters together within the filterString.

Solution:
To chain multiple filters in a filter string, use Java syntax with logic operators like && and || for ‘and’/‘or’.

Example: (operation == "Create" && application == "Active Directory")

Alternative Object Classes:
For broader JML tracking, consider using Lifecycle Event objects if Lifecycle Manager is enabled, as they provide structured data on identity changes like onboarding, offboarding, and transfers.

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