Data Governance in the Age of Generative AI

The article discusses the importance of effective data governance in the age of generative AI and provides practical strategies for organizations to establish a robust data governance framework.

Specifically, the article covers:

• The four pillars of effective data governance: data visibility, access control, quality assurance, and ownership
• Strategies for improving data visibility, such as creating a centralized data catalog and following an iterative, value-based approach
• Approaches to balancing data access and security, including a federated access management framework and investing in robust access control tools
• Techniques for ensuring data quality, like appointing data quality stewards, implementing automated quality controls, and establishing data quality KPIs
• Building a data-driven culture by securing buy-in, shifting to a data stewardship mindset, and making data governance a C-suite priority
• Conclusion: Effective data governance is an ongoing process that can unlock significant competitive advantages for organizations