Jia Khee Lim
In 2024, most analyst firms such as Forrester have called out GenAI as a game-changer in posing data security challenges, especially with regard to protecting sensitive information. Organisations have already implemented ML and simpler forms of AI, typically based on data from a single data source.
But as noted by McKinsey, an organisation’s data architecture needs to integrate data from various sources, including unstructured data stores, for GenAI to be functional, trusted, and scalable.
With this data used to power GenAI applications, dispersed across potentially hundreds of systems, how does an organisation practically implement and enforce sensitive data access controls? How do you do that with real time and historical data to ensure privacy and at scale?
Join us to learn how the data fabric architecture of Denodo enables you to create global security policies in the logical layer that allows for implementing semantic security rules across the data, independent of the source and destination systems being used – ensuring a trusted, secure data foundation for GenAI applications.
