1. State of North Dakota Information Technology Department (ITD) July 2012

2. Agenda  Background  What is the “Master Person Index”?  And why do we need it?

3. Background  ND SLDS P20W Non-federated single system with multiple agency warehouses and datasets o K12 (IES grant ndSLEDS) Warehouse o PS SFSF collection (will grow to be its own warehouse) o PS (IES grant) o Workforce (WDQI grant) warehouse o Workforce Accountability Programs o Adult Ed/ CTE/ WIA Vocational Rehab datasets

4. FEDES National Student Clearinghouse SLDS: K12 Domain SLDS: HE Domain SLDS: Work Force Domain SLDS

5. WIA Youth Career and Tech Ed Adult Ed Immunizations (Health) Workforce Training Programs SLDS Vocation Rehab Vital Records (Health)

6. Student Identifiers  Identifiers K-12 State Student ID exists ○ EC establishing Postsecondary ID exists K12 to PS matching ○ o 85-90% historical matching based off name, dob, HS ○ o Move to early PS assignment (9th – 12 grade)

7. Workforce  Workforce (UI data) Limited quality on employees (25-30% no-name) No DOB  K12-WF Linkage Needed for research Very few K12 SSN present

8. P20 Identifier Expansion  Needed a solution to match WITHIN and ACROSS various agencies and datasets.  Need a more powerful and flexible set of matching algorithms Algorithms configurable based on the quality and elements available in the source  Need to protect the confidentiality of the underlying data Secured and Private matching across domains  Need to match both in real-time and in batch Enterprise Entity Resolutions Systems and an agency MDM initiative and too difficult to use in the SLDS environment  Gather all of the unique combinations to identifying information associated with one person

9. Identifier Requirements  K-12 SLDS required a Unique ID system  Issued and managed a Unique ID for Students and Staff  This worked well within the K-12 environment  Matching within K-12 was possible and easier

10. Expanding into P-20  Using the Unique ID system was not sufficient to match across various agencies and datasets.  Need a more powerful set of matching algorithms.  Still require the assignment of ID’s across agencies.  Needs to protect the confidentiality of the underlying data.  Need to match both in real-time and in batch.  Gather all of the unique combinations to identifying information associated with one person.

11. What is it?  The Master Person Identifier System (MPIS) represents a next generation matching system, which uses the power of likelihood algorithms to integrate person records.

12. Functionality of the MPIS  Extended to cover non-K12 submitting systems.  All K-12 MPI algorithms brought into P20 MPI and extended with additional matching algorithms; as examples, ‘Nickname’, Keyboard distance matching.  Matching keys made extensible to any field(s) from submitting systems.  Batch processing enabled from Workforce, Immunization and Higher Ed related systems.

13. MPIS Process

14. MPIS Structure

15. Why do you need a MPIS?  Data coming from various sources (agencies and organizations)  Data standards differ  Key identifiers differ from the sources  Need to protect the confidentiality of the data  Need to be able to quickly match and generate datasets or analysis across domains and sources

16. Why do you need a MPIS? (continued)  The MPI table becomes the glue connecting all of the various sources and systems.  Matching criteria critical for performance measurements across agencies.  Enables tracking of a “person” rather than a child, student, staff, worker or adult.

17. Expansions  Probabilistic (thresholding) settings on matches Confidence levels based on matching needs  Case Management Resolving near matches on critical data sets ○ (student matches from EC, DHS, K12, PS)  Matching Workbench Run matching algorithms for what-if analysis

18. Q & A  Any questions?

19. Presenters Mr. Tracy Korsmo State of North Dakota Information Technology Department (ITD) tkorsmo@nd.gov Mr. Eddie Parker Otis Educational Systems “Data Management Architect” eddie.parker@otised.com