Definition[edit | edit source]

Data governance

Overview[edit | edit source]

It is an emerging discipline with an evolving definition. The discipline embodies a convergence of data quality, data management, business process management, and risk management surrounding the handling of data within an organization. Through data governance, organizations are looking to exercise positive control over the processes and methods used by their data stewards to handle data.

The definition of data governance includes management across the complete data life cycle, whether the data is at rest, in motion, in incomplete stages, or transactions. To maximize its benefit, data governance must also consider the issues of privacy and security of individuals of all ages, individuals as companies, and companies as companies.

Data governance is needed to address important issues in the new global Internet Big Data economy. For example, many businesses provide a data hosting platform for data that is generated by the users of the system. While governance policies and processes from the point of view of the data hosting company are commonplace, the issue of governance and control rights of the data providers is new.[3]

Data governance is a set of processes that ensures that important data assets are formally managed throughout the enterprise. Data governance ensures that data can be trusted and that people can be made accountable for any adverse event that happens because of low data quality. It is about putting people in charge of fixing and preventing issues with data so that the enterprise can become more efficient.

Data governance also describes an evolutionary process for a company, altering the company's way of thinking and setting up the processes to handle information so that it may be utilized by the entire organization.

References[edit | edit source]

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