Responding to in-house and third-party software applications with limited integration capabilities, the Ohio DOT (ODOT) developed a data governance framework to improve data management efficiencies and reduce data duplication.
Subarea: Governance (A.5)
Element: All (A.5.a– A.5.d)
ODOT contracted a study to measure the department’s maturity in data governance. A survey was created and administered to key ODOT data business owners. Recommendations from this study were to create data a governance framework and supporting policy and standards.
Step 2: Establish Governance FrameworkA data governance structure was defined with oversight by the Chief Data Officer and a Data Governance Committee.
Step 3: Create Governance Standards, Roles, and ResponsibilitiesThe Data Governance Committee led a project to implement enterprise data standards, define governance roles and responsibilities, and establish metadata management practices.
Step 4 (Future State): Treat Data as an AssetThrough increased awareness of governance processes, make ODOT a data-driven organization emphasizing data quality, availability, integrity, and usability.
Consistent quality, availability, integrity and usability of data
LeadershipExecutive endorsement and vision from onset
IT collaboration and integration in project
Technical expertise in big data and industry standards
CoordinationIdentify and leverage data governance champions
Cross-department communication
Change management focus on value derived from the change
