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- Data governance has executive-level sponsorship with direct CEO supportdirect CIO and Executive Leadership support. Executive-level decision-makers view data as a strategic asset. Management understands and appreciates the role of data governance – and commits personnel and resources.
- Business users take an active role in data strategy and delivery
- Data stewards emerge as the primary implementers of data management strategy and work directly with cross-functional teams to enact data quality standards
- A data quality or data governance group works directly with data stewards,
application developers and database administrators - Organization has "zero defect" policies for data collection and
management
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- Management understands and appreciates the role of data governance – and commits personnel and resources
- Executive-level decision-makers begin to view data as a strategic asset
- Data stewards emerge as the primary implementers of data management strategy and work directly with cross-functional teams to enact data quality standards
Policies
- New initiatives are only approved after careful consideration of how the initiatives will impact the existing data infrastructure
- Automated policies are in place to ensure that data remains consistent, accurate and reliable throughout the enterprise
- A service oriented architecture (SOA) encapsulates business rules for data quality and identity management
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- Real-time activities and preventive data quality rules and processes emerge
- Data governance processes are built into the foundation of CDI, PDM and other solutions
- Data metrics are sometimes measured against industry standards to provide
insight into areas needing improvement - SDLC
- Goals shift from problem correction to prevention
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- Data quality and data integration tools are standardized across the organization
- All aspects of the organization use standard business rules created and maintained by designated data stewards
- Data is continuously inspected – and any deviations from standards are resolved immediately
- Data models capture the business meaning and technical details of all corporate common data elements
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- A data stewardship group maintains corporate common data definitions and business
rules - Service-oriented architecture becomes the enterprise standard
- Ongoing data monitoring helps the company campus maintain data integrity
- More real-time processing is available and data quality functionality is shared across different operation modesoperational solutions
Risk and Reward
- Risk: Low. Master data tightly controlled across the enterprise, allowing the organization to maintain high-quality information about employees, student, research, facilities, financials, and assets.
- Rewards: High. Corporate data practices can lead to a better
understanding about an organization's current business landscape – allowing management to have full confidence in all data-based decisions