Data Governance Newsletter (February 2025)

Data Governance: What is it?

Given the daily headlines that aim to redefine governance, we'll clarify what data governance means at the University of Denver.

What is Data Governance?

Data governance defines how the University of Denver manages, protects and leverages data. Our framework promotes data integrity, security and compliance while fostering a culture of stewardship and collaboration. The university can approve data governance policies, strategies, and major initiatives. It also provides high-level guidance and oversight.

Who's Data Governance?

Data Governance is guided by a Steering Committee chaired by our chief data officer, Mike Furno. The committee includes representatives from the Office of the Provost, Information Technology, Compliance and Risk Management, University Finance, Office of the Registrar, Advancement, Data Domain Chairs and Institutional Research.

• Data Governance Principles
• Data shall be easy to find, quick to understand and simple to compare.
• Data shall be consistent and predictable, avoiding the harm caused by conflicting versions.
• Data shall be maintained securely.
• Data shall be processed consistent with the University's Privacy Policy and applicable data privacy laws.

Learn more about data governance at DU.

Data Domain Groups: Where is my silo?

Data Governance Roles

Data governance also requires defining work scopes into specific roles and responsibilities. Over the next 12 months, division leaders and the steering committee will identify, convene and train individuals for their roles.

Roles | Responsibilities

• Steering Committee: Provides overall strategic direction and makes policy decisions.
• Data Trustees: Establish data ownership, set priorities and ensure institutional goals are aligned.
• Data Stewards: Implement policies, standards and guidelines, ensuring data quality, security and compliance.
• Data Custodians: Manage the technical aspects of data storage, security and access control.
• Data Users: Ensure responsible and ethical use of data for academic, research and administrative purposes.
• Data Governance Liaisons: Facilitate communication between data governance committees and academic or research units.

Most of these roles are already defined by their job descriptions. Domain governance aims to build a community of practices that will improve our operations and enhance the reliability and use of data.

Learn more about data governance at DU.

Words to AI By: A Pocket Guide for the Use of Generative Artificial Intelligence

Artificial Intelligence (AI) is transforming the business landscape, offering unprecedented opportunities for innovation and efficiency. As generative AI tools become increasingly integrated into University operations, it is crucial to use them responsibly. Here are four practical guidelines for adopting AI ethically, effectively and sustainably.

1. Check with the Technology Review Committee

   All new AI tools, applications or software products—and the purchase of additional modules for existing software—must be initiated through the Technology Solution Center and undergo a thorough New Technology Review (See University Policy IT 13.10.040-Technology Acquisition). Any generative AI systems, applications, or software products that process, analyze or move confidential data require a security review before they are acquired, even if the software is free. This review will help ensure the security and privacy of University data.

2. Protect University Data

   Never enter sensitive, protected, regulated or confidential data into AI tools. Using publicly available generative AI tools to analyze confidential data is prohibited without prior security and privacy review. This includes personally identifiable employee data, FERPA-covered student data and HIPAA-covered patient information and may include research that is not publicly available. Some grantors, including the National Institutes of Health , have policies prohibiting the using generative AI tools in analyzing or reviewing grant applications or proposals. Information shared with publicly available generative AI tools may expose sensitive information to unauthorized parties or violate data use agreements. Please see University Policy IT 13.10.051-Data Classification for definitions of confidential data and its use for more information.

3. Respect Intellectual Property – You are Responsible for Content Accuracy and Ownership

   Don't assume public data is free of intellectual property rights. AI-generated content may be misleading or inaccurate. Generative AI technology may create citations to content that does not exist. Responses from generative AI tools may contain content and materials from other authors and may be copyrighted. The tool user is responsible for reviewing the accuracy and ownership of any AI-generated content.

4. Academic Integrity

   Instructors should contact the Office of Teaching and Learning for guidance on how generative AI tools intersect with academic honesty. (See Honor Code in the Student Manual for University policy.)

OpEx & Data Governance

From Broad Engagement to Action

One of the many OpEx working groups was a group focusing on data. Several recommendations from that working group have been shared and enthusiastically embraced by the Data Governance Steering Committee. Top recommendations include:

• Improve Communication from Leadership: Hence the first edition of Bytes and PiecesData Governance Newsletter.
• Formalize and Create Reporting (dotted lines and processes) from Academic Units to Institutional Research: The aim is to restructure the Data Analyst role and improve the support and development of the role toward better access to data. The Data Governance Steering Committee agrees with its importance and will submit a formal proposal to support the recommendation.
• Implement a cross-unit knowledge-sharing initiative to share data solutions and best practices, making a beautiful transition to the following article–IMAC is back!

Many other suggestions are also being reviewed, but these were the top three.

IMAC is back!

DU's Information, Measurement and Analysis Council has been revived! IMAC is a collaborative group focused on data governance, enhancing data literacy and coordinating analytic efforts across campus. We invite all analysts, report developers, data managers, leaders who guide systems and data decisions, and those who heavily use data to inform decision-making to attend and contribute to this initiative.

Our first meeting, held on January 15, was a great success! We provided an update on data governance at DU and gathered valuable insights on how to evolve IMAC to serve our campus community better.

Now we want to hear from you.

Please take a few minutes to complete the IMAC survey by March 7, 2025. Your input will help shape our future direction and ensure IMAC remains a valuable resource for data governance, reporting and analytics collaboration across campus.

Take Survey

If you're interested in joining the conversation or learning more, please email lisa.redfield@du.edu to receive the meeting details and to be included in future communications.

We'll use your feedback to plan our next IMAC meeting, which is scheduled for June—stay tuned for details.

Thank you for participating in this effort to strengthen data governance and coordination at DU. We'd love to have you join us!