Data at Carnegie Mellon University

Carnegie Mellon University (CMU) is committed to supporting an information-driven culture that balances security and risk mitigation while maximizing the value of our institution's data. Responsible data management should enable us to provide the right data to the right people at the right time with the right level of access.

Data@CMU is a collaborative program initiated by the Office of the CIO and Institutional Effectiveness and Planning in partnership with campus administrative and academic leaders and stakeholders. This collaborative effort aims to eliminate data silos and develop services to enable the strategic use of our institutional data to make informed decisions and enhance growth. 

To encourage data-informed decision-making, it is critical that we empower authorized data consumers to view, understand, analyze, and access the data within a given administrative business area. Data domain and subject matter experts are working to provide clear data definitions and mechanisms, like the Data Analytics Sharing Hub, to facilitate data access through a shared, centralized process. 

These business units will continue their partnership with IT experts to ensure data quality, provide standard business reports, and deliver data integration services for campus IT administrators. The foundational steps to define and refine data will move us toward the longer-term vision of self-service data access and analytics.

As data stewards and custodians, it is our responsibility to ensure the appropriate levels of data access to maintain security and privacy while enabling data use to inform organizational goals. A Data Stewardship Council (DSC) was established to oversee and govern university data assets. In partnership with Computing Services, the DSC defines processes to facilitate access for authorized use and guidelines for the responsible storage and use of data.

Working with the DSC, Computing Services is developing services to assist custodians of university administrative systems to:

• Define data elements within their system
• Leverage a centralized access request process to evaluate and fulfill data access requests
• Analyze access requests to identify opportunities for automation
• Identify data quality issues to inform corrective steps

A community creates opportunities for learning, sharing knowledge, and collaborating on projects. This support network brings together those with common roles or similar interests in developing, managing, organizing, and using data to inform decision-making.