What is Data Governance?
Data governance is the process of setting and enforcing priorities for managing and using data as a strategic asset. A data governance body with authority and oversight over the management of agency data assets is a key piece of data infrastructure. These bodies are commonly called by such names as Data Governance Boards, Data Councils, or Data Strategy Teams. The data governance body establishes policies, procedures, and roles for developing, overseeing, and coordinating data management policy and helps prioritize data resource allocations to answer agency key questions and meet stakeholder needs.
Mission Statement
In aligning with the priorities established for ±¬ÁϹÏ, the mission of the Data Governance Program is to establish and uphold a robust framework for data governance that ensures the effective management, security, and ethical use of data across the university. Through clear policies, responsible stewardship, and continuous improvement, we strive to maintain the integrity, availability, and privacy of data, enabling informed decision-making, supporting academic excellence, and fostering trust among students, faculty, staff, and stakeholders.
Data Hub
This site is intended to provide vital operational information for leadership roles at the University. The dashboard can be viewed and accessed using MIDAS credentials. The dashboards are connected to Banner and refresh automatically.
Frequently Asked Questions
Data governance ensures data quality, security, compliance, and enables informed decision-making.
Data management focuses on the technical aspects of handling data, while data governance establishes policies, standards, and accountability frameworks for managing data effectively and responsibly.
Data analytics involves extracting insights from data, while data governance focuses on ensuring data quality, security, compliance, and integrity.
Data governance is typically considered a program rather than a project. It's an ongoing initiative that involves establishing and maintaining policies, processes, and controls for managing data effectively within an organization. While specific data governance activities may be structured as projects (e.g., implementing a data governance framework, establishing data quality controls), the overall effort to govern data is continuous and requires long-term commitment and investment.
Common measures of data governance success include improved data quality, enhanced regulatory compliance, increased data security, and streamlined data processes.
Data governance is not solely a technical solution; it's not just about tools or technology but encompasses policies, processes, and people.
Data governance best practices include establishing clear policies and roles, fostering organizational alignment, prioritizing data quality, ensuring regulatory compliance, and fostering a culture of data stewardship and accountability.