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Data Modernization

Bridging the gap from data to decisions.

Data Governance: The Foundation of Data Modernization 

  • What is Data Modernization? – Intentional transformation of how UND collects, secure, integrates, analyze, and uses data to support timely decision-making, agility, and futureproofing for advanced analytics and AI​.
  • What is Data Governance? – It’s a framework that establish ownership, standards, definitions, and responsible use as it scales.

What is Data Governance? 

Data Governance ensures that the university’s data assets, risks, and responsibilities are aligned with institutional goals. It provides a structured framework that promotes strategic decision‑making, transparency, collaboration, and accountability around UND’s data—academic, operational, and research.

Data plays a critical role in UND’s operations, compliance, planning, research, teaching, and student success. As data sources grow in volume and complexity, so does the need for high‑quality, secure, and accessible data across the university.

UND leadership initiated the development of a formal data governance framework to address data silos, quality inconsistencies, security issues, and the need for standardized policies. This effort aims to strengthen collaboration, expand institutional understanding of data stewardship, and promote consistent, ethical use of data for decision‑making across UND.

Vision 

Bridging the gap from data to decisions. 

Mission

To empower the university’s decision‑making through the responsible use of trustworthy, unified, and accessible data.

Key Objectives

  1. Alignment with UND LEADS: Data governance ensures UND’s data practices support the university’s mission, strategic plan, and long‑term goals.
  2. Improved Decision‑Making: A clearly defined governance framework improves how UND collects, uses, shares, and interprets data, resulting in stronger, more consistent institutional decisions.
  3. Transparency & Collaboration: The governance structure brings together stakeholders across campus to develop shared definitions, policies, and standards.
  4. Risk Management: Data governance helps identify and mitigate risks related to data quality, access, security, and compliance.
  5. Efficiency & Effectiveness: By standardizing processes and data definitions, the university reduces redundancy and improves operational efficiency.
  6. Change Management: Governance supports the responsible introduction of new data systems, tools, and processes across units.

Mission, Purpose, and Guiding Principles

Purpose of Data Governance at UND

  • Ensure institutional and research data are stored, secured, and accessible to support UND’s mission and strategic goals.
  • Define roles and responsibilities for the creation, use, and security of data.
  • Collaborate with IT Governance and other shared governance structures.
  • Provide training across campus on responsible data practices.
  • Establish and enforce ethical data‑use standards, including partnerships with external agencies.

Guiding Principles

  • Ownership & Stewardship: Clear data owners and stewards for each data domain.
  • Single Source of Truth: Authoritative systems provide consistent definitions and data lineage.
  • Data Quality Management: Integrity maintained across the data lifecycle.
  • Security: Classification and protection aligned with sensitivity and risk.
  • Consistent Definitions: A shared glossary to promote common understanding.

Governance in Action 

UND’s data governance framework includes executive oversight, institutional sponsors, a Data Governance Council, and two specialized Steering Committees so decisions and ownership are clear, coordinated, and consistent across the institution.

Governance Structure

UND’s governance model ensures the right people are involved at the right stages—from high‑level strategy to operational implementation.

  • Executive Sponsorship: Provides institutional direction, authority, and resource support.
  • Institutional Sponsorship: Oversees the data governance program, translates strategy into implementation, and leads cross‑functional alignment.
  • Data Governance Council: A cross‑campus leadership group responsible for setting policies, approving definitions, prioritizing initiatives, and ensuring representation across major data domains.

Data Governance Council 

  • Executive Sponsors
    • President 
    • Vice President of Acadmic Affairs and Provost
    • Vice President for Finance & Operations and COO
    • Vice President for Marketing & Communications
    • Vice President for Student Affairs
    • VP & Dean, School of Medicine & Health Sciences
    • VP for Research & Economic Development
  • Institutional Sponsors 
    • Chief Data Officer
    • Associate Vice President and Chief Information Officer 

Steering Committees

Institutional (Operational) Data Governance Steering Committee

  • Focus Areas:
    • Student, HR, finance, facilities, and other core administrative data
    • Data quality standards
    • Access and usage guidelines
    • Operational reporting and analytics consistency
    • System ownership and lifecycle oversight
    • Resolution of cross‑unit data issues
  • Members include representatives from:
    • Chief Data Officer, UIT Security, Institutional Effectiveness, Resource Planning & Allocation, Student Affairs, TTaDA, HR, Auxiliary Services, Data Science, Dean of Students, Registrar, Health Sciences, Athletics, VP of Research, and College Data Fellows.

Research Data Governance Steering Committee

  • Focus Areas:
    • Research datasets (scholarly, grant‑related, compliance‑regulated)
    • Research data standards, ethics, and security
    • Federal sponsor alignment
    • Data Management Plan support
    • Oversight of research data lifecycle and secondary uses
    • Risk management and issue resolution
  • Members include representatives from:
    • Chief Data Officer, UIT Security, Research Affairs, Library Digital Initiatives, Clinical Campuses, Research & Sponsored Programs, Data Science, Registrar, Dean of Students, Health Sciences, Athletics, and College Data Fellows.

Operational Roles

  • Data Owners: Hold authority and accountability for specific data domains.
  • Data Stewards: Implement data policies, support data quality and security, and collaborate with owners and custodians.
  • Data Custodians: Provide technical management, protection, and maintenance of data systems.
  • Data Users: All UND community members who interact with institutional data; responsible for protecting it.

Your Role in Data Modernization

We encourage active participation and valuable input from all stakeholders. If you have questions or would like to share feedback, please email mandi.tyryfter@und.edu. 

 

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