Data governance is a collection of processes, policies, standards, and metrics that ensure the effective and efficient use of information in enabling an organization to achieve its goals. It is a principled approach to managing data during its life cycle, from acquisition to use to disposal. The goal of data governance is to promote the availability, quality, and security of an organizations data through different policies and standards.
Data governance encompasses the people, processes, and information technology required to create a consistent and proper handling of an organizations data across the business enterprise. It provides all data management practices with the necessary foundation, strategy, and structure needed to ensure that data is managed as an asset and transformed into meaningful information.
The key focus areas of data governance include availability, usability, consistency, data integrity, data security, and standards compliance. Data governance initiatives improve the quality of data by assigning a team responsible for datas accuracy, completeness, consistency, timeliness, validity, and uniqueness. This team usually consists of executive leadership, project management, line-of-business managers, and data stewards.
Data governance is important because it establishes processes that ensure data quality and security across an organization. It helps organizations maximize the value of their data, manage risks, and reduce costs. Effective data governance programs seek to improve data quality, reduce data silos, ensure compliance and security, and distribute data access appropriately.
In summary, data governance is a process of managing the availability, usability, integrity, and security of the data in enterprise systems, based on internal data standards and policies that also control. It is a collection of processes, policies, standards, and metrics that ensure the effective and efficient use of information in enabling an organization to achieve its goals.
