Data Governance Best Practices


Data Governance is a critical piece in an organization’s overall management, quality, and compliance initiatives.  The gathering, safekeeping, translating, checking and disseminating of data require a rigid process and these processes are not born overnight. People who work in Data Governance are keen on ensuring that their prime asset, the “data”, is put to good and productive use.

In order to make these processes efficient and effective, there are a number of best practices that an enterprise can incorporate. Please note that this is not the end-all and be-all of Data Governance practices but it is informative and educational enough to apply to your own organization.  You have to remember that the concept of Data Governance is the same for all, it is only the system and how the data is needed by the various departments that changes depending on the enterprise.

  • There should be transparency of goals within the organization. Each representative must be able to identify how the data can affect their department.
  • Goals should be achievable, measurable and quantifiable
  • A solid reporting system should be made; intervals on when these reports need to be generated should also be identified
  • Proper education and authority should be assigned to everyone involved
  • There should be a clear cut process of escalating data updates/disputes/variances
  • There should be a clear work-around time for when these data updates/disputes/variances will be worked on
  • People who will carry on Data Governance tasks should be broken down so that they can be easily identified as to who will do what
  • There should be a regular touch-up on Data Governance so that the people are updated of new processes/systems
  • Proper training needs to be given on a regular basis (monthly, quarterly, yearly, depending on the organization)
  • There should be a set of individuals from the Data Governance team that will regularly attend enterprise meetings to ensure that Data Governance goals are aligned with the goals of the organization as a whole
  • Metadata structure should be given importance and this provides key understanding of how data should be used
  • Good governance metrics should be put in place and good governance output should be properly recognized
  • There should be an executive responsible for monitoring and measuring the success of Data Governance

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