Data Governance

DATA GOVERNANCE

Data governance is the collection of processes, policies, roles, metrics, and standards that ensures an effective and efficient use of information. Also, it helps establish data management processes that keep our data secured, private, accurate, and usable throughout the data life cycle.

The data governance framework is built on collaboration and requires the support of individuals and teams, such as University Analytics, the Data Governance Office and departments all across campus to ensure we achieve data governance at UTA. The framework is organized into 5 distinct groups:

• Chief Analytics and Data Officer
  • Dr. Pete Smith is UTA’s CAO/CDO, which in his role, he leads UTA’s data analytics strategy, driving data-related business changes. Additionally, he is responsible for university-wide governance and utilization of information as an asset.
• Data Governance Office
  • Lisa Creed, Manager of Partnerships & Data Governance, oversees the UTA data governance program’s development, architecture, and administration. Her role includes the socialization and education of organizations across campus on data and data governance.
• Executive Community
  • ­The executive community Includes senior University leaders who have oversight of the DGO, moreover, supports alignment between university strategic initiatives and governance program goals. Also, the executive community has the determining vote in situations where an agreement cannot be met between the data governance body and departmental bodies.
• Data Maverick (Stewardship) Community
  • The community of Data Mavericks Includes individuals in departments across campus, representing a community of both data consumers and data producers, who on a day-to-day basis, ensure data governance practices and data policies are being followed. They collaborate with University Analytics and other departments to resolve data quality issues and identify opportunities for continuous improvement.
• Subject Matter Experts (SMEs)
  • ­­A SME is any person on campus knowledgeable or considered the go-to person about a particular data topic or data process. He/she are individuals, not roles, within the data governance program.

OUR APPROACH

The Data Governance Office at UTA achieves success from tailoring the scope of the data governance program to the unique needs of UTA. And, in taking an iterative, Agile approach, to governance, the DGO can build momentum, trust in the process, and leverage it for further success.

Agile Data Governance is data producers and consumers creating and improving data assets by iteratively capturing knowledge and working together so that everyone can benefit. Instead of taking a top-down method with many formal structures, which we feel impedes progress, UTA takes more of a grassroots approach to governance.

DATA INTEGRITY

Data integrity is the overall accuracy, completeness, consistency, and validity of our data. With so many of our decisions today depending on the ability to rely on trusted and accurate data, it is essential to build data integrity into the mission and directives of the data governance program.

In order to ensure data integrity within global, state, and national reporting, as well as analytics and UA data products, the UA team works closely with data producers, subject matter experts, data stewards, and OIT on resolving data quality issues and, in some cases, offering recommendations for process improvement.

In addition, UA places importance in providing governance throughout the development and offering of data products, such as:

• Provide a single, reliable, trusted source of data enabling self-service tools, such as dashboards, reports, and models.
• For better understanding, all self-service tools Include definitions, context if needed, and a brief describing to the user of the tool’s overall purpose.
• Regular data quality monitoring and reporting, as well as an active engagement with the Data Maverick Community to ensure data integrity in our source systems.
• Provides training and education so users across campus understand what data is available, how to use it, and how to request access.
• Audits of the SAS environment (UA Data Warehouse) are completed regularly to ensure accessibility is secure and appropriate.
• Quality standards for source code are used for all data management and analysis, supporting a lean process, and supporting efficient production and use of UTA resources.