Data Governance

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Data governance is an emerging quality control discipline for managing data integrity, quality, and access in data-driven environments. While no consensus framework yet exists, data governance oversight committees are a frequently cited strategy to monitor enterprise data in healthcare and biomedical research. Furthermore, data governance relates to privacy, confidentiality and security by overseeing policies, practices and controls used by an organization to mitigate risk and protect patient health information. [1]

Provided below are three frequently cited definitions of data governance:

The Data Governance Institute defines data governance as “...a system of decision rights and accountabilities for information-related processes, executed according to agreed upon models which describe who can take what actions with what information, and when, under what circumstances, using what methods." [2]

The Master Data Management Institute defines data governance as "...the formal orchestration of people, process, and technology to enable an organization to leverage data as an enterprise asset." [3]

IBM's Data Governance Council defines data governance as “... a quality control discipline for accessing, managing, monitoring, maintaining, and protecting organization information.” [1]

References

  1. 1.0 1.1 International Business Machines IBM. The IBM data governance blueprint: Leveraging best practices and proven technologies. http://www-935.ibm.com/services/us/cio/pdf/data-governance-best-practices.pdf
  2. Data Governance Institute. Definition of Data Governance. http://www.datagovernance.com/adg_data_governance_definition/
  3. Master Data Management (MDM) Institute. MDM and Data Governance: Readiness Assessment. http://tcdii.com/PDF/A%20Summary%20Practical%20Guide%20to%20Systems%20Integrators%20&%20Consultancies%20for%20MDM%20&%20DG.pdf