Data and Data Governance
Why Data Governance?
Colleges, hospitals and units tend to treat university and Wexner Medical Center data as individual assets. A lack of common processes, definitions, training, documentation and user support result in little trust in our collective data, and an inability to make accurate, important and timely business decisions across the enterprise.
Data governance builds trust in the institution’s information assets by establishing shared understanding through data availability, quality and usability. It mitigates risk and increases the value of data as an institutional asset.
How much data governance is needed at Ohio State? It’s simple: We need as little as possible to meet both enterprise-wide and individual college, hospital and unit needs.
Data Governance and the Enterprise Project
The Enterprise Project is a business transformation and system implementation to enable the institution’s mission. It includes the replacement of Ohio State’s core administrative technology with Workday, transforming business processes for optimal efficiency and effectiveness and improving decision-making through consolidated and trusted data.
Data governance is a core component of the Enterprise Project’s efforts to enable the institution’s teaching, research, service and patient care missions. The project gives Ohio State an opportunity to foster a collaborative institutional culture around our data. By moving from a siloed approach to a collective effort, our data will enable better decision making, decrease compliance risk and be viewed and treated as a trusted institutional asset.
Benefits of Data Governance
Data Governance helps us move from a state where there is little trust in data to a future state where there is confidence in the data and it is trusted for use in making sound business decisions.
|currEnt state||Future state|
|An isolated focus on data security||An inclusive approach to availability and transparency|
|Institutional data silos||A shared responsibility across the enterprise|
|A lack of data documentation||Consistent data definitions in standard formats|
|Inconsistent training and support||Consistent training across the institution|
|Time spent on operational reporting||More time for data analytics and decisions support|
|Reactively fixing incorrect data||Gaining efficiencies through validating data upon entry|
|Little trust in data||Strong trust in data|
Shared Guiding Principles
The Business Intelligence, Analytics and Reporting Guiding Principles (BAR) that were developed to help determine BAR workstream activities within the Enterprise Project’s scope, also serve as a foundation for Data Governance.
Do you have specific data governance questions? Please contact Laura Gast, Data Governance and Policy Lead.