Data Governance projects increase data quality by delegating responsibility for data accuracy, completeness, consistency, timeliness, validity, and originality to a team. Executive leadership, project management, line-of-business managers, and data stewards are common members of this team. The team typically employs some sort of corporate data tracking and improvement technique, such as Six Sigma, as well as tools for data mapping, profiling, cleansing, and monitoring.
Data Governance initiatives may seek to achieve a variety of goals, including improving visibility to internal and external customers (such as supply chain management), complying with regulatory law, improving operations following rapid company growth or corporate mergers, or enhancing the efficiency of enterprise knowledge workers by reducing confusion and error and broadening their scope of knowledge. Many data governance projects are also influenced by previous attempts to improve information quality at the departmental level, which resulted in incongruent and redundant data quality processes.
Most major corporations have numerous applications and databases that cannot simply share data. As a result, knowledge employees in large businesses frequently lack access to the data they require to conduct their jobs effectively. When they do gain access to the data, the quality of the data may be subpar. These issues can be minimised by establishing a data governance process or corporate data authority (person or area responsible for determining how to continue in the best interests of the business when a data issue emerges).
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