Data Mesh TV: Quantifying Risk on a Mesh

In a recent episode of Data Mesh TV, Gavin Grounds and Adrian Estala discussed the challenges and methodologies of quantifying risk in the context of a Data Mesh framework. They emphasized moving beyond simplistic risk categories like low, medium, and high to a more precise numeric quantification, which allows for a comprehensive view of an organization's risk portfolio. The Data Mesh provides a standardized framework to tackle the complexities of managing risk, particularly with diverse and unstructured data sources. By implementing a points-based system to evaluate the value and mission-critical nature of data assets, organizations can make informed decisions on whether to increase or decrease the risk associated with specific data products. This approach has significant implications for data democratization and monetization, as it enables clearer decision-making and the potential to leverage data for new revenue streams.