Institutional Research & Effectiveness

Data Governance Overview

Aligning with Wright State University's Bridge Strategic Plan 2023-2025, data governance establishes a structured approach to data management, safeguards data assets and promotes data quality, integrity, and accessibility.  It includes policies, standards, and practices to ensure the effective use and management of data.


Data governance development is ongoing.  During the 2023-2024 academic year, the Data Governance Council is working on identifying data stewardship responsibilities and communities, developing procedures to support data management, and communicating updates to the campus community as outlined in the strategic plan.


  • Improving institutional efficiency.
  • Encouraging collaboration and data literacy.
  • Creating and maintaining a culture of data-informed decisions making.
  • Building stakeholder trust by ensuring their data is handled responsibly and transparently.
  • Provides the foundation for an institutional data repository, a core component of business intelligence, establishing an environment for enhanced reporting, data analysis, modeling, forecasting, and a single source of historical truth. 


Data governance is executed by people, enabled by processes, and supported by technology. It drives a culture of data-informed decision making through accountability and data literacy education. Four critical success factors, or pillars, support the framework of data governance. Stewardship, quality, access, and standards pillars of data governance are build on people, processes and technology.  Data literacy and training is required in all areas.  Together this supports a culture of data-informed decision making.

  • Stewardship:  A role for campus individuals accountable for managing processes and data assets, and ensuring data is used appropriately and effectively. Stewards act as custodians of the data and are accountable for maintaining its integrity and safeguarding it from misuse or unauthorized access.

  • Quality: Ensures data is accurate, reliable, consistent, and relevant for its intended purposes. Data stewards are involved in activities to maintain high data quality and efficient processes.

  • Access: The process of retrieving and interacting with data, facilitating data-driven decision-making and enabling applications to leverage the underlying data effectively. Includes evaluating the institutional balance of data availability with privacy, compliance, and security.

  • Standards: Policies, guidelines, and specifications that define data and include structure, format, classification, and exchange across different systems. The primary purpose of data standards is to ensure consistency, interoperability, and quality of data across various processes, applications, and stakeholders.

Roles & Responsibilities

Executive Committee

Individual members of the President’s Cabinet who provide program oversight, high-level project approval and prioritization, policy approval, and project funding. 

Data Governance Council

Council Members ensure and support the effective management of data assets and project portfolios of the University by establishing procedures and standards, making policy recommendations, advocating for appropriate resources, and guiding and monitoring data governance efforts.

Data Trustees

University officials with responsibility over institutional data and processes as designated by the Data Governance Council. Data trustees are accountable for managing, protecting, and ensuring the integrity and usefulness of institutional data and for upholding Wright State University policies, state laws, and federal laws applicable to the institutional data and the processes that support them.

Data stewards

University staff who help define, implement, and oversee data management policies and procedures within their specific data domain. Institutional data stewards have delegated responsibility for all aspects of how data is acquired, used, stored and protected throughout the full data life cycle from acquisition through disposition.

Data Domains & Access

Data domains are high-level categories of institutional data/processes, as designated by the Data Governance Council.