Data Quality Showcase

1. Data Quality Showcase The many angles of Data Quality in Kansas Kathy Gosa, Director, KSDE Kelly Holder, Data Analyst, KSDE Kateri Grillot, Senior Trainer, KSDE 25th Annual STATS-DC 2012 Data Conference July 11, 2012

2. Kansas Education Landscape • 286 school districts- over 1500 schools • Approximately 520,000 (Pre K-12) students • Combination of rural vs. urban • About 37,000 educators • Issue approximately 20,000 licenses annually • Local control – approximately 17 different student information systems • Elected Board – appointed commissioner

3. Achieving Data Quality • Input • Training • Communication • Common User Experience Quality • Management • Governance • Master Data Management • SW Development Standards • Data Audits • Use • Reports • Dashboards

4. Input • Training • Communication • Common User Experience Input: Training • New user training • In-person • Online • On-demand • Training before and during collections • Data Quality Certification Program

5. DQC Program Overview

6. Input • Training • Communication • Common User Experience Input: Communication • Listserv • Deadlines/reminders • Question of the Week • Conference calls • HelpDesk • Tech support via phone • Reporting guidance via email

7. Input • Training • Communication • Common User Experience Input: User ExperienceStandards • Single sign-on via Common Authentication System

8. Input • Training • Communication • Common User Experience Input: User ExperienceStandards

9. Input • KIDS New Staff Training • Pre-Collection Workshops • Data Coordinator DQC Track • Weekly KIDSINFO Listserv • KIDS HelpDesk • Planned Changes • KIDS Collection v8.0 • Training • Communication • Common User Experience

10. Management • Governance • Master Data Management • SW Development Standards • Data Audits Management: Governance • KSDE implemented a Data Governance Program in 2005. • This program includes definition and responsibilities for data ownership and data stewardship, outlines the goals and objectives for the Board, the Data Steward Workgroup, and the Data Request Review Board.

11. Management • Governance • Master Data Management • SW Development Standards • Data Audits Management: Governance • Data Quality is a guiding principle of the Data Governance Board. • The Data Governance Board is focused on policy considerations for all data across the agency. This includes: • source data collections; • KSDE Enterprise Data Warehouse; • reporting access including federal and legislative, local, and research requests; • security of data; • data verification; • deadlines; • communication regarding data and policy; • establishing certification requirements; and • master data management.

12. Management • Governance • Master Data Management • SW Development Standards • Data Audits Management: Master Data Management • KSDE’s Enterprise Data System includes integration of data through implementation of Master Data Management processes to ensure core data are captured, defined, and used consistently across the enterprise.

13. Management • Governance • Master Data Management • SW Development Standards • Data Audits Management: Master Data Management • Identify those data elements collected and stored by the agency that should be considered the master source for specified purposes. • Document policies and procedures related to Master Data Management so expectations related to this are clear and can be enforced.

14. Management • Governance • Master Data Management • SW Development Standards • Data Audits Management: Master Data Management • Ensure that whenever a system managed by the agency includes information consistent with a defined master data element, the system will use the master data element rather than collecting the data element separately. • This is to ensure: • No redundant data collections occur. • Data are used consistently and appropriately. • Data systems can be connected allowing sharing of data across the agency.

15. Management • Governance • Master Data Management • SW Development Standards • Data Audits Management: SW Development Standards • Software Development standards not only lead to efficiencies but also contribute to data quality through data integration & communication. • Consistent technologies (e.g., Microsoft .Net, SQL Server) • Technical Design standards • Naming Conventions • Harvest Logic • Code Reusability

16. Management • Governance • Master Data Management • SW Development Standards • Data Audits Management: Data Audits • Data Audit Framework • Purpose: Implement a systemic process for using data audits to improve data quality. • Process Ownership: Data Governance Board. • Process Design: Builds on other initiatives (KIDS, DQC, EDS).

17. Management • Governance • Master Data Management • SW Development Standards • Data Audits Management: Data Audits • Data Audit Cycle: • Identification • Evaluation • Analysis • Use

18. Management • Governance • Master Data Management • SW Development Standards • Data Audits Management: Data Audits • Data Audit Reports Identify: • Data Quantity and complexity — critical for project scoping • Active data — data that should be in scope for the project • Inactive data — data that needs to be properly flagged in the source system • Source data issues and problems that can cause load errors

19. Management • Governance • Master Data Management • SW Development Standards • Data Audits Management: Data Audits • Data Audit Reports Identify: • Missing, incorrect, or unusual values • Duplicate records within a source and/or across sources • Distribution frequencies of common configurations (i.e., AYP School, Funding School, AYP Student Subgroup)

20. Management • Governance • Master Data Management • SW Development Standards • Data Audits Management: Data Audits • Data Audits provide recommendations for: • Level of Detail • Data Cleansing • Configuration Considerations • Opportunities for Professional Development

21. Management • Governance • Master Data Management • SW Development Standards • Data Audits Management: Data Audits • Completed Data Audits • KIDS (core student data collection) • Educator • Assessment • Migrant • Planned Data Audits • Career and Tech Ed • Special Education

22. Management • DGB reviews annual planned changes & DRRB monitors release of KIDS data • KIDS web services used to populate core student data in all student data collection and reporting systems (e.g., SPED, CTE, Migrant, CNW, School Finance, Assessments) • KIDS Data Audits are used internally and externally to improve quality • Governance • Master Data Management • SW Development Standards • Data Audits

23. Use • Reports • Dashboards Use: Reports Fictitious Data

24. Use • Reports • Dashboards Use: Dashboards Fictitious Data

25. Use • Approximately 40 different user reports in 8 different categories • Dashboards are the subject of required homework exercises in the DQC Program • Reports • Dashboards Fictitious Data

26. How do you know when its impacting data quality at the SEA? • The trend of repeated data audits shows decrease in issues. • State’s fiscal auditors have observed a reduction in reporting errors. • Data owners and data stewards comment that the data are becoming more reliable. • There is a reduction in AYP Helpdesk call volume.

27. How do you know when its impacting data quality in the LEA? • “Our school district set a new record for low percentage of errors on our 9/20 data.”

28. Questions? • Kathy Gosa, kgosa@ksde.org • Kelly Holder, kholder@ksde.org • Kateri Grillot, kgrillot@ksde.org