Primarily risk mitigation, data governance protects data and information as an enterprise asset (including archive strategies). This includes the structures, people, processes, and technology required to create consistent and proper handling of data across the enterprise.
Data governance is concerned with measuring and monitoring compliance to data standards and business rules.
Benefits of Data Governance
- Reduce cost by eliminating redundant effort to maintain master data and avoid duplicates
- Ensure data ownership
- Improve data security
- Decrease the risk of regulatory fines
- Increase the quality of master data
- Increase consistency and confidence in decision making
- Accelerate availability of up-to-date master data in the business network
- Provide transparency on who has changed what, when & why
- Convert manual processes to system guided processes with workflow approval
Data management is the operational execution of controls and processes. This includes the creation and maintenance of data objects, their fields and their content, as well as the creation and maintenance of business rules that are defined according to the data standards set in the governance process.
Data Management can exist without Data Governance, but it cannot mature or scale.
SimpleData Governance aims to reduce the complexity of data governance by focusing on what is most important from a data domain or object perspective. SimpleData Governance is a three phase approach, where we work with the business to:
- Determine the current data management and data governance state.
- Make implicit structures or controls explicit - so that this allows for control.
- Translate this into a future governance framework as part of the business strategy.
From Data Objects to Governance
Start with the Data Objects and the various tasks, roles and processes orbiting them. Then define the roles, responsibilities and processes so that every level becomes structured measurable, and controllable.
Without control and consistency at the base, processes utilising multiple data objects will fail. When maintenance and control start from the object level, domain quality is possible.
Roles require structure, policies & procedures so that governance can be embedded and risk mitigated.
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