data governance guiding principles
Data governance can be a topic of hardship for any enterprise without such a program, but also with one in the works or at different maturity stages. There are a lot of success factors which need to be met to coast through and achieve a highly mature data governance program while the variables keep changing. To get a data governance program started on the right path or have a course correction for one which is already underway, I believe the following 10 guiding principles should be followed:

  1. Data is a strategic enterprise asset and should be managed as such
  2. Data governance is a program and a business discipline, not a project, which needs an ongoing investment, support, and exposure
  3. Data governance is the foundation upon all enterprise information initiatives are built
  4. Data governance and stewardship are a shared responsibility between business and IT
  5. There is a common glossary with shared and approved business term and data definitions with a clear curatorship and ownership process
  6. There is only one version of the truth for enterprise data which is actively managed and trustworthy
  7. Data management needs to comply with legal and regulatory requirements, internal policies, and follow industry best practices and standards
  8. Enterprise data are accessible and understood by relevant roles as needed in order to carry out their duties
  9. Accountability for different data management practices is clearly defined, assigned, and managed
  10. Data governance efforts, goals and objectives, priorities, decisions, and deliverables (procedures, processes, standards, policies, framework, etc.) are always communicated and made available to the entire enterprise

What are the guiding principles of your data governance program? Do you think they can all be followed?

{"email":"Email address invalid","url":"Website address invalid","required":"Required field missing"}

About the author 

George Firican

George Firican is the Director of Data Governance and Business Intelligence at the University of British Columbia, which is ranked among the top 20 public universities in the world. His passion for data led him towards award-winning program implementations in the data governance, data quality, and business intelligence fields. Due to his desire for continuous improvement and knowledge sharing, he founded LightsOnData, a website which offers free templates, definitions, best practices, articles and other useful resources to help with data governance and data management questions and challenges. He also has over twelve years of project management and business/technical analysis experience in the higher education, fundraising, software and web development, and e-commerce industries.

You may also like:

7 principles of data quality management
>