Data Architecture for the Age of Generative AI

As organizations move from analytics to AI-driven products and services, data architecture must evolve, propelling demand for one of the most important jobs of the 2020s - data architects. In this session, Aurelien Chu shows how to consider what an operational data flow looks like when it powers AI workflows from product to operations to staffing to finance. We'll discuss what such a flow looks like in the constrained environment of a startup like Eskwelabs, and then how to apply similar principles for larger institutions. We'll also discuss what might drive the demand for new jobs in data engineering, data architecture, and systems design with AI.