Data Governance: 

"Planning, oversight, and control over management of data and the use of data and data related sources".*

*definition from the Data Management Association International (DAMA)


Data Governance Quick Links

Data Governance Lifecycle Management & Foundational Activities

DAMA Wheel & Triangle

Data Governance at WSU


Several data systems1 exist which the university community can use to inform decision-making, planning and reporting.  The mission of the Data Governance Council (DGC) is to provide oversight to these data systems to ensure data integrity, best practices in data management, reporting standards, information consistency, and security access.  In addition, the Data Governance Council is charged (see Appendix A for official charge) with identifying data and reporting needs related to strategic planning priorities and the sharing of business knowledge across divisions to ensure data and reporting optimization related to the latest business practices within units.  The Data Governance Council provides compliance with the Higher Learning Commission (HLC) requirements related to institutional data used for accreditation.

Data Governance Principles:

  1. Data must be recognized as a valued and strategic enterprise asset that must be managed effectively.   
    •  Accurate & timely data are the critical foundation for effective decision-making, strategic development, customer-service and are the basis for reducing cost and maximizing returns.
  2. Data must have clearly defined accountability.       
    • Data are a by-product if business practice.  Therefore, data owners, data stewards, and data custodians must control classification and use of data including change management.
  3. Data must be seen as cross-functional and not siloed.     
    •  Data exists in an ecosystem of cross-functional dependencies where shared business practice knowledge is necessary for data processing and deployment.
  4. Data integrity must be defined and managed consistently across the data life-cycle.       
    • Data must have defined business use validity, reliability, and quality from data entry to data retention.
  5. Data must be managed to follow internal and external rules.       
    • Security over data compliance and access to data is required to protect data of individuals and the institution.

1 Data systems encompass Wichita State University ERP system-Ellucian Banner, non-Banner Enterprise systems and managed data systems including Business Intelligence and Predictive Modeling (BIPM), University Assessment Data Storage (UADS) and External Reporting Data (ERD).  While largely dependent upon transactional databases (e.g., Banner), managed data systems are curated data configurations designed for ETLs, data quality audits, reporting and statistical analysis, and include data customizations, aggregation, imputation, forecasting, simulations, and AI related machine learning.