1. The many angles of Data Quality in Kansas
Data Quality Showcase
The many angles of Data Quality in Kansas
Data Quality Showcase: The many angles of Data Quality in Kansas
Achieving data quality is not as straightforward as it may appear on the surface – and to be effective, efforts to achieve quality need to be approached from many angles.  In Kansas, we have found that data quality requires a systemic approach that addresses common quality issues on a variety of fronts, both technical and nontechnical. In this session, you will hear how Kansas has approached data quality systemically through data quality audits, training, dashboard development, master data management practices, and software application edits and standards.
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
Use
Reports
Dashboards
Quality
Management
Governance
Master Data Management
SW Development Standards
Data Audits

4. Input: Training New user 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 Data Entry
Source System Data Stewardship, Data Calendar, Audit Checklists, Error Prevention
Data Coordinator
All of Data Entry Curriculum Plus: Submission Practices, Error Correction Procedures
Administrator
Sign Off Process, AYP, Funding, Hiring Procedures, Information Sharing Among Staff
Assessments & Accountability
State Assessment Data, Reports,
AYP
Building a Culture of Quality Data,
Student Privacy, Resource Navigation
Data Ethics, Annual Re-Certification
Assessments & Accountability Data
Career & Technical Education Data
Enrollment & Transportation Data
Special Education Data
Migrant Student Data
Graduation & Dropout Data

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

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

8. Input: User Experience Standards
Training
Communication
Common User Experience
Input: User Experience Standards

9. Input Training Communication Common User Experience
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;
deadlines;
KSDE Enterprise Data Warehouse;
communication regarding data and policy;
reporting access including federal and legislative, local, and research requests;
establishing certification requirements; and
master data management.
security of data;
data verification;

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

18. Management: Data Audits
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: Data Audits
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: Data Audits
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: Data Audits
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 Governance Master Data Management SW Development Standards
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 Reports Dashboards
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,