Data mesh is both a technical and organizational approach to managing and accessing data. We were lucky enough to have Zhamak Dehghani, who coined the term data mesh, join us for this discussion on how the data mesh impacts data scientists.
By having this decentralized approach and treating data as a product, data is able to be exposed and shared with those that need it the most, including the data scientists. Zhamak said, “To get value from data, particularly for analytical purposes, when we want to make predictions or we want to discover trends, we have to aggregate and centralize data in one place, under the control of one set of technologies and specifically under the control of a centralized team.”
The question of data ownership is a huge pain point for data scientists. However, with the data mesh architecture, scientists are able to access data where it lives and better contribute to the overall business goals. In a conversation moderated by Sophie Watkins of Red Hat, the panel comprising, Daniel Abadi, professor of Computer Science at University of Maryland, Max Schultze of Zalando, and Zhamak Dehghani of Thoughtworks, discuss pain points, best practices, and the overall principles of data mesh.