0. Data Governance Process
Rick Rozzelle
Center for Educational Leadership and Technology
April 2013

1. Agenda 1. Definition and Purpose of Data Governance
2. Goals and Strategies for Data Governance
3. Structure and Roles of Data Governance
4. Data Categories for a Local Education Agency
5. Data Dictionary
6. Data Quality Tools and Templates

2. Data Governance - Definition
Data Governance establishes the foundation (policies, standards, architecture, decision-making structure, issue-resolution process) for collecting, managing, and releasing data for improved quality, accessibility, and use.

3. Data Governance: Purpose
To establish the policies and procedures governing data-related matters for the school district. This includes who is accountable for various portions or aspects of the data, including its accuracy, accessibility, consistency, completeness, and updating.
To define processes concerning how the data is to be collected, stored, archived, backed up, shared, and protected from mishaps, theft, or attack.

4. Data Governance: Purpose (cont.)
To develop a set of standards and procedures that defines how the data is to be used by authorized personnel.
To implement a set of controls and audit procedures that ensures ongoing compliance with government regulations.

5. 10 Goals of Data Governance
Improve data quality
Improve understanding of data within the school district
Increase use of data to make program and policy decisions
Enable easier access to data – for all constituencies
Enable consistent and high-quality data releases
Increase data security
Reduce operational friction
Protect the needs of data stakeholders
Reduce costs and increase effectiveness through coordination of efforts
Ensure transparency of processes

6. Data Governance ~ Key Strategies
Increase accountability for data accuracy
Establish management support and involvement
Establish a Data Governance Policy for the school district
Assign Data Managers/Stewards and Data Quality Director
Assign one designated Data Steward for each data element
Eliminate redundant data
Collect data one time
Store data once - share data from its designated source system
Identify the system of record for all data elements
Reduce collection of/reliance on aggregate data
Establish a calendar to manage/control data collection/reporting events
Document data processes
Define all data elements
Ensure processes are documented, standardized and repeatable
Standardize data processes from year to year
Reduce manual manipulation of data

7. Data Governance ~ Key Strategies
Manage data releases
Establish a clear process for managing data releases
Identify the official source of data for all external reporting
Communicate all data decisions/changes
Involve the schools in the process – communicate with them regularly
Establish an annual cycle for requesting all changes to data collections
Coordinate all database revisions through the Data Management Working Group
Make data quality a priority
Establish proactive data quality trending processes among all Data Stewards
Maintain and actively pursue a data issues log and issue resolution process
Increase the use of student-level data for external reporting

8. Data Governance ~ Key Strategies
Build with the future in mind
Document the current-state information architecture
Design the future-state information architecture
Make all major decisions based upon the future-state architecture
Make data security everyone’s job
Provide training program for all new employees
Require that all employees sign the security policy annually
Engage Data Stewards in security decisions for their data
Require that data is treated as a Department asset – not an IT asset and not a program-area asset.

9. Processes guide data needs and IT architecture (form follows function)
Guiding Philosophy
Processes guide data needs and IT architecture (form follows function)
How things get done (processes) are central to determining data needs and how computer systems should be designed and integrated (information architecture).
Conversely, designing systems without understanding the processes and process owners creates silos, duplicated data and disjointed systems.
Computer systems, if implemented without process definitions, have limited value.
Process ownership, and the corresponding data ownership, belong in the departments/program areas, not IT.

10. Data Governance Structure
Tier 1 – Data Policy Committee (DPC) comprised of appropriate executive management policy makers.
Tier 2 – Data Management
Working Group (DMWG) comprised of Data Stewards, led by a Data Quality Director.
Tier 3 – Temporary work teams assigned to address data issues.

11. Data Quality Director Roles
Ensure the data stewards are performing their duties.
Manage and chair the DMWG.
Maintain a data collection and reporting calendar.
Maintain a critical data issues log.
Convene working groups of data stewards to address critical data issues that involve multiple program areas.
Facilitate collaboration between program areas.
Review database revisions with the DMWG.

12. Data Steward Roles
Determines how data is defined, collected, quality assured, and reported.
Establishes access rights and security levels.
Reviews and approves data releases.
Identifies and recommends solutions for data issues.
Verifies that data elements are recorded and kept current in the data collection and reporting calendar.
Establishes procedures to ensure the data is properly collected.
Participates on the Data Management Committee.

13. Tier 1 – DPC Roles Establishes data governance policy.
Assigns data stewards and members of the Data Management Working Group.
Resolves data and process issues referred by the Data Management Working Group.
Approves policies as recommended by the Data Management Working Group.

14. Tier 2 - DMWG Roles
Provides support and strategy for data sharing and management.
Establishes policies for the proper management and use of data.
Is the sponsor organization for the data warehouse.
Provides leadership and direction in maintaining a data collection calendar and data inventory.
Works with CIO to establish a data architecture (standards, policies, processes, and database structures) for the State.
Reviews all requests for new data structures and application systems and recommends their approval.

15. Data Categories Data Category Data Category School Directory Data
Curriculum and Instruction Data
Student Demographic Data
Career and Technical Education Data
Attendance and Enrollment Data
Professional Development Data
School Instructional Programs, Course Data
English Language Learner Data
Immigrant and Migrant Student Data
Assessment Data
Special Education Data
Federal Programs and Grants Data
Data Category
Supplementary Education Services Data
Early Childhood Data
Financial and Budget Data
School Staff and Certification Data (Highly Qualified)
Child Nutrition and Economic Status Data
Discipline, Dropout, Graduation Rate Data
Course Scheduling Information
Grades/Marks Information
Facilities Information
Health Conditions
Transportation/Boundary Data

16. Issue Resolution Identifying Solutions Escalation Process Supt.
Data
Policy Committee
(Leadership)
Issue Escalation and Accountability
Data Management
Working Group
Data Steward
Data Users

17. Data Management Working Group
Resolving Issues
Data Resolution Process
Issue Corrected
Can solve
issue?
Data User
Yes
Data Steward
Tier 1 No
Identifies
Data Issue
Single
Category
Can solve
issue?
What type
of issue?
Multiple
Category
Yes
Data Management Working Group No
Tier 2
Data Quality Director
Application
Issue No
Can solve
issue?
Data Policy Committee
(Leadership Team)
Tier 3
Application Sponsor
Yes 17

18. Center for Educational Leadership and Technology
Questions
Rick Rozzelle
Center for Educational Leadership and Technology
(774)