Data Governance Custodial Committee
DGCC provides a data governance structure for UWM, allowing the campus, via the committee’s work, to prioritize and ensure consistency of data reporting, to provide guidance and oversight in developing campus-wide definitions of important data terms and ensuring their transparency in reports, and to develop actionable plans and priorities for the future of business intelligence at UWM— including the capital, personnel, technical, and political resources needed to realize these goals. Through
consultation with campus leadership in the form of ITAC, DGCC will pursue these goals, with a membership drawn from subject matter experts within business units with an understanding of current data needs and aspirational goals, central IT staff with a pragmatic understanding of the technical environment, and appropriate members from administrative units to provide a perspective of the
mission and long-term institutional vision.
Build trust in University data through intentional investments in data literacy while collaboratively developing and broadly sharing data assets and knowledge.
The UWM data environment has evolved from a few data experts in influential central roles to a fragmented model where many decentralized data analysts often operate without any formal data training. This structure promotes unit-first reporting activities which lead to data disparities and distrust across units which prevent us from moving collaboratively toward being a data-driven University. More
importantly, this structure obscures our total costs and investments in data reporting and prevents our resources from being effectively coordinated to maximum their impact. In our current reality…
• Not all schools/colleges and departments have data analysts. This leads to haves and have-nots and a culture of black-market data requests in areas without dedicated staff.
• In areas with dedicated data analysts, many are not formally trained in the nuances of our data and may create potentially erroneous reports as well-meaning “citizen analysts.”
• Units with knowledgeable data analysts, will likely waste significant amounts of time explaining or validating conflicting numbers created by these citizen analysts.
• A thirst for “the right” data leads to unit-level report creation and shadow systems which duplicate functionality and deprive the University of a comprehensive picture of data needs.
• As units become more insular, changes in processes or data elements will not always filter down to individual units who maintain existing reports and data, leading to misleading or bad data.
• Even when these redundant reports and data are updated, these activities happen multiple times, taxing already-limited resources and increasing the likelihood of errors.
From an organizational perspective, our decentralized data culture wastes time and money and often prevents us from making the tough, proactive decisions about improved data tools and structures that are necessary to transform our data into a competitive advantage. From the user perspective, this culture prevents coordinated approaches to asking and answering questions with data, understanding
shared data needs alongside existing data resources, and strategically investing in the tools and employee training to collaboratively develop new shared data assets.
In general terms, our goals prioritize shared investments, transparency, and intentional decisions about the people, tools, and resources dedicated to campus data reporting. We envision a data culture where central resources are devoted to promoting a University-wide perspective and understanding unit-level data needs. By empowering and supporting existing data analysts, we can foster campus-wide data literacy, ensure data consistency, and focus our limited resources on creating shared dashboards and reports to address common priorities and problems.
A Commitment to Data Literacy
• A well-defined and transparent method for consumers to learn about and contribute to existing definitions of common University reporting terms, reports, and dashboards.
• Communication methods for the campus community to broadcast or ask questions about process or data changes which may impact logic or existing data assets
• Dashboard standards to streamline dashboard creation and simplify user adoption
Intentional Data Resourcing
• Integration of data and data support needs assessments into the purchase of all new vendor contracts or software purchases.
• A “reporting catalog” which lists available analytics tools, support contacts, available reports and data sets, and the use case for the tool.
• A set of Procurement rules and standardized process for purchasing reporting tools which accounts for total cost of ownership and support needs.
A Focus on Shared Reporting Assets
• Curated data models for less experienced report authors and consumers to create personalized reports and dashboards.
• Increase the number of shared campus dashboards by the constant exploration and enumeration of reporting needs.
The DGCC is committed to the belief that data should be treated as a highly prized asset of the University. The decentralized distribution of data analysts across our University necessitates that a governing body constantly guard and protect this asset. By creating an environment in which data is defined, consistent and available, we will create trust and encourage the campus to make data informed