Data governance refers to a consistent and goal-driven handling process of the wide variety of big data across an organization such as a research institution or a business enterprise. A particular governance model includes nearly everything that is directly or indirectly related to the data like people, processes, or even IT systems. Often goals are defined on the various levels of an organization when working with data that in turn helps in the acceptance of governance processes by users that need to follow them. In many cases, before governance is discussed within an organization, the data handling is often very inconsistent and no one has the overview.
In more detail a governance model can be seen as a type of control that ensures that all data generated by people or IT systems meets certain data standards. These standards can be defined depending on the data and scope such as a business rule, important data definitions, or also data integrity constraints of the data model itself. An important aspect of the governance is to perform individual data stewardship or to have data governors that use data quality monitoring during all processes. The key goal is to improve data quality by communicating errors back to operational data users within the organization such as data analysts. Another aspect of this is to take corrective actions with technical support teams of IT software if certain data is not produced or stored according to defined data formats or metadata standards.
Data Governance Details
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