[tabby title=»Performed»]
Level 1: Performed
Data governance functions are performed.
Governance often begins as project-based, aligned with development and operation of application data stores; for example, validation of logical and physical data models.
Ownership, stewardship, and accountability for data sets are primarily project-based assignments.
Example Work Products
- Governance process documentation
- Evidence of implemented governance processes Description of data governance roles and responsibilities
[tabby title=»Managed»]
Level 2: Managed
2.1A defined and documented data governance structure is in place.
Data Lifecycle Management provides information about the business processes in the organization that deal with data management activities. This information is used to help identify the data governance management needs.
Data Management Strategy provides guidance on development of data management priorities and strategy, which is used to help define the scope of data governance.
2.2 Governance roles, responsibilities, and accountabilities are established for data subject area by priority, as stated in the business or data strategy.
2.3 Data subject area representatives participate in data governance and associated processes.
Data Management Function provides details on roles and responsibilities related to data management.
2.4 Data governance follows defined policies, processes, and standards.
2.5 A review process is established and followed to evaluate and improve data governance.
Example Work Products
- Data governance charter
- Data governance policy
- Documented data governance processes and standards, including the decision process, issue resolution, and operations
- Roles, responsibilities, and accountability matrix
- Governance body meeting minutes
[tabby title=»Defined»]
Level 3: Defined
3.1 An organization-wide data governance structure and rollout plan is established with executive sponsorship.
Standard conflict and issue resolution processes for data governance are developed and adopted across the organization.
The data governance charter(s) and operational rules establish the method for resolving conflicts and the criteria for escalation.
Refer to Communications, which provides guidance on effective communications to support governance implementation and management.
3.2 Executive level organization-wide data governance is operational for the organization’s high-priority subject areas.
Data governance is responsible for managing governance execution and providing liaison among business owners, data stewards, and IT.
3.3 Data governance includes representatives from all business units, which are suppliers or consumers of high-priority data subject areas.
Governance roles, responsibilities, and accountability are established for subject areas at the organization level.
3.4 Standard data governance policies and processes are followed.
Data governance decisions, policies, and processes are communicated across
the organization.
Data compliance processes and corresponding data governance roles are established and enforced organization-wide. The organization should have specified data governance activity categories and decision authorities by governance body level. For example, major changes to data standards should be reviewed and approved by the executive data governance council, as they have a long-term e ect on the target data architecture.
3.5 Data governance determines and approves appropriate metrics to evaluate effectiveness of governance activities.
Approved data governance metrics measure the progress and expansion of governance activities and accomplishments, and alignment with the organiza- tion’s business objectives. Corrective action is taken when metrics are out of alignment or indicate insu cient progress against business objectives.
3.6 An evaluation process is established for refining data governance to align with changing business priorities and to expand as needed to encompass new functions and domains.
Data governance adjusts its activities affected by modification or addition of new business processes and data, new regulatory rules, or new internal compliance requirements. It is important to ensure consistent accountability within the organization as it grows, changes, and evolves.
3.7 Classroom, mentoring, e-learning, or on-the-job training in data governance processes is required for new governance members and other stakeholders.
Data governance bodies determine what type of training is needed for each role for new members.
3.8 Data governance activities and results are analyzed against objectives periodically and reported to executive management.
Example Work Products
- An executive-level data governance charter
- A organization-wide data governance rollout plan
- Metrics to evaluate data governance effectiveness
- Evidence of the adoption of data governance policies and processes Data governance training materials
- Governance meeting minutes
- Reports of decisions and action items
[tabby title=»Measured»]
4.1 Statistical and other quantitative techniques are applied to determine if governance efforts are changing organizational behaviors appropriately.
4.2 Adjustments to data governance activities and structure are made based on analysis results.
Example Work Products
- Metrics-based analytical performance reports
- Executive reports of governance effectiveness
[tabby title=»Optimized»]
5.1 External governance structures and industry case studies are evaluated for best practices and lessons learned, providing ideas for improvements.
5.2 The data governance structure is communicated to the peer industry as a model of best practice.
5.3 Data governance processes are continually refined and improved.
Example Work Products
- Internal presentations or white papers referencing the data governance model as an industry best practice
- Reports evidencing continual governance improvements
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