What is data governance?
Data governance is a collection of practices and processes which helps to ensure the formal management of data assets within an organization.
Why is data stewardship at U-M important?
U-M has a long-standing data stewardship framework that supports access to and sharing of institutional data.
This framework, which is governed by SPG 601.12 (Institutional Data Resource Management Policy), plays a vital role in advancing the institution’s research, teaching, and clinical missions; allowing for decision-making by university leaders; and presenting opportunities for sharing and collaborating with other universities, institutions, and consortia.
Why is there a need to make changes to data governance at U-M?
U-M’s current data governance practices are decentralized, often ad hoc, with no consistency across data domains and between schools, colleges, units, and departments. Data governance occurs in pockets, and there has been an increasing need for overall coordination across the institution.
The result is that access to data is unclear, sharing and review processes are slow and inconsistent, audit trails are minimal to non-existent, and requesters end up collecting and storing redundant data sets, which increases risk to the university and costs time and money.
Are there other factors driving the need for change?
Yes, there are several. The university has a need for better data for institutional decision-making. Cloud computing, external service providers, big data, data science, and analytics are resulting in more diverse and decentralized data. And various laws and regulations—along with privacy and ethical considerations—have put an increased focus on appropriately protecting and using data.
Which offices are sponsoring the revitalized data governance effort?
The Office of the Vice President for Information Technology and Chief Information Officer and the Office of the Provost cosponsored the initiative.
What is the goal of the revitalized data governance plan?
The goal is to increase access to and usability of institutional data while minimizing risk to the university.
This approach will require a culture of data citizenship and literacy where data quality assessments are performed and training is available on how to identify appropriate data sources and forms and the ethical use of data. It also will mean greater responsibility by faculty and staff for the appropriate use and protection of that data as described in university policies and practices created by data stewards.
What will the future of data governance at U-M look like?
It will have consistent guidelines and practices related to data access, data quality and use, and data for decision-making. The tenets and practices will focus on enterprise data, which is used for accreditation, compliance, and decisions impacting the institution, and it will be scalable to the myriad databases, data sets, and data warehouses existing centrally and within units.
When did the revitalization effort begin?
It began in Spring 2020.
Which group initially led the effort?
VPIT-CIO Ravi Pendse and Provost Susan Collins charged the Data Governance Council to make recommendations, which included laying the groundwork for what it would take to revitalize data governance at U-M.
What were the Data Governance Council’s accomplishments?
- creating and maintaining information about shareable data sets to help requesters find what data sets and data fields are available for request.
- providing a ticketing system to manage request submission, processing, approval, and reporting for access to datasets.
- developing and documenting processes and guidelines for data request submission, processing, approvals, escalations, reviews and audit, in order to maintain quality and consistency.
- conducting a review of all roles involved in the data request process and streamlining the role structure.
- creating a forum for data stewards that will enable data steward education, support common practices, and build relationships around a shared campus data vision.
- conducting discovery of current access to data and recording historical information to enable audits of data sets that are currently being shared.
What recommendations were made?
A key Data Governance Council recommendation was to disband itself and to create a permanent Data Governance Advisory Committee.
Other recommendations were to expand the request and auditing system to include more data sets and types, and to create a catalog of university data to help identify “system of record” data and to document differences across campus.
Are other academic institutions undertaking similar work?
Yes, and the Data Governance Council’s recommendations are consistent with what other academic institutions are doing.
Various institutions resetting their data governance include Indiana University, Penn State, Purdue University, Stanford University, The Ohio State University, The University of Texas at Austin, University of California Los Angeles, University of Illinois, University of Maryland, University of Virginia, University of Washington, and University of Wisconsin.
Data Governance Advisory Committee
What is the Data Governance Advisory Committee doing?
In Spring 2022, the Data Governance Advisory Committee began meeting and responding to the Data Governance Council’s report, which provides recommendations for future actions for data governance success, along with a status of the projects initiated under the Council’s guidance.
Advisory Committee responsibilities involve recommending business practices for data governance that span data steward areas and ensuring these align with university strategic objectives.
Who serves on the Data Governance Advisory Committee?
Members serving on the Advisory Committee are respected and trusted individuals with experience and understanding of university data and business practices at a high level, as well as the potential impact of decisions made in data governance.
What type of data is the Data Governance Advisory Committee focusing on?
The Data Governance Advisory Committee is initially focusing on enterprise data, which is a critically important asset to the university, since time and resources are needed to safely manage and share the data through careful and effective data modeling, storage, and access provisioning. Specifically, the committee is directing its efforts at data access, data quality and use, and data for decision-making.
Where should university community members direct questions related to data governance?