Vision:
Our vision is that institutional data are securely accessible, understood, and trusted and are used in a consistent, responsible, and meaningful manner in order to increase interoperability, ensure reliability, and inform decision making in our community.
Goals to help achieve that vision:
- Manage like a master: Enable and support the collection and management of master data elements for broad community use. Addresses interoperability, reliability, consistency, secure accessibility.
- Improve intelligence and involvement: build data literacy for staff across the university including data users, business process owners, and technology providers. Addresses understood, meaningful, reliable.
- Connect and converse: support the change that is required to build community where data activities are appreciated and data are appropriately shared. Addresses trusted, responsible, and reliable, and informing.
Activities that help achieve these goals:
- Create master data models as a foundation for broad-use master data collections.
- Build data collections that the master data models describe and ensure people and processes are in place to keep collections current.
- Enable a management and dissemination platform for data stewards to create and update master data for downstream users to consume.
- Improve data awareness in process design by consulting with project teams before processes and platforms are designed, built, or acquired.
- Formalize data requirements gathering as part of the technology investment process to ensure appropriate data capture, reporting, and storage capabilities.
- Increase the data usage and handling skills of staff across the university to reduce anxiety about working with data and improve data processes, products, and output.
- Provide a foundation for collaboration across various silos and data deserts to help manage expectations and improve trust and data sharing.
- Create robust change management and communication strategies to bring awareness to the importance of data activities.
- Connect data users and analysts across the enterprise to build a community and increase trust and reduce unnecessary duplication.