Director of Data Science and Engineering
Many enterprises are investing in their next-generation data platforms with the hope of democratizing data at scale to provide business insights and ultimately make automated intelligent decisions. Data platforms based on the data lake architecture have common failure modes that lead to unfulfilled promises at scale.
In this talk, Ken shares his observations on the failure modes of the centralized paradigm of a data lake or its predecessor data warehouse.
Ken introduces Data Mesh, a next-generation data platform paradigm that draws on modern distributed systems architecture: considering business domains as the first-class concerns, applying platform thinking to create self-service data infrastructure, and treating data domains as products.