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

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

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.

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.

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.

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

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

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

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.

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.

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.

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.

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.

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.

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.

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

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

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

Center for Educational Leadership and Technology Questions Rick Rozzelle Center for Educational Leadership and Technology rrozzelle@celtcorp.com (774) 2492112