MDM for SIS Advisory September 12, 2008. CU Goals for MDM  De-Dup Constituent Data for Campus Solutions Implementation  Synchronize Constituent Information.

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Presentation transcript:

MDM for SIS Advisory September 12, 2008

CU Goals for MDM  De-Dup Constituent Data for Campus Solutions Implementation  Synchronize Constituent Information HCM 8.9 HCM 8.9 Campus Solutions 9.0 Campus Solutions 9.0 CRM 9.0 CRM 9.0  Publish Constituent Information Campus Directories Campus Directories Identity (user) Provisioning Identity (user) Provisioning Numerous administrative & academic systems Numerous administrative & academic systems  Retire Expensive Custom Solutions Complex pseudo hubs Complex pseudo hubs Redundant business logic (affiliations!)Redundant business logic (affiliations!) Limited integration capabilities (nightly!)Limited integration capabilities (nightly!) Expensive to maintain & leverageExpensive to maintain & leverage Various “exception” constituent provisioning systems Various “exception” constituent provisioning systems

Before…

Before… Lots of awkward, point to point, batch oriented (daily at best!) Flat-File based integration

UCM as a Data Scrubbing Engine Pre-Conversion Legacy Existing SIS Cleansing/Matching Server(s) Data Quality Engine PSFT CS New SIS

PSFTHCM PSFTCS SCM OSS PSFTCRM Employee ID: Student ID: UIDAppID 1ASCLSCCPSFT CRM ASCLSCCPSFT HCM ASCLSCCPSFT CS Universal ID: 1ASCLSCC Applicant ID:  Stores all Student identifiers for the operational applications connected to UCM  Provides critical mappings used for data synchronization, reporting, and analytics  Supports 1-to-many cases in which multiple Student records exist in an application that map to one master Student record How UCM Establishes a Unique Identity: Cross Referencing

Survivorship Rules: –Preserves master data –Are highly configurable Determines: –Update privileges –Contention resolution Granular Rules: –Object based rules –Source confidence rules –Temporal rules –Attribute groups –Attribute group fields Survivorship Rules – Level of Trust

What are the implications and next steps?  We will need campus support for data cleanup.  The campus community group will take a lead in working through rules and configurations.  We must understand our data governance model.

Questions?