Data Leadership Collaborative: Creating a Data Governance Culture

machine learning
    Data Society      
machine learning
    June 15, 2022          
machine learning              News
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Orginial article published for Data Leadership Collaborative

Why do people quietly run for the exits when they hear the words “data governance?” 

I’ve seen it many times. The trepidation is real. It feels daunting. It is by no measure a small project. Implementing a data governance framework across a large organization can be measured in years, not months or quarters.

And yet data governance continues to rise in importance. The introduction of the General Data Protection Regulation (GDPR) framework in the EU and the California Consumer Privacy Act (CPAA) are both clear signals of the greater regulation that’s coming for data usage and data management. Healthcare and pharmaceutical companies have worked under tight data regulations for years, but retail organizations as a whole, to choose one example, have yet to fully awaken to the implications of closely governing and implementing data security protocols for their data and that of their customers. 

Data-driven cultures require governance

Data governance isn’t an optional add-on for a successful data culture, but a core component of developing one. Standardized guidance and principles are essential to determine:

  • how to use data
  • where to store data
  • how to label data
  • how to access data
  • how to update data
  • what to do in case of a data breach
  • how to look for data bias


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