  Current Cloud solutions for Edge Computing are inefficient for data-centric
applications, as they focus on the IaaS/PaaS level and they miss the data
modeling and operations perspective. Consequently, Edge Computing opportunities
are lost due to cumbersome and data assets-agnostic processes for end-to-end
deployment over the Cloud-to-Edge continuum. In this paper, we introduce MEDAL,
an intelligent Cloud-to-Edge Data Fabric to support Data Operations
(DataOps)across the continuum and to automate management and orchestration
operations over a combined view of the data and the resource layer. MEDAL
facilitates building and managing data workflows on top of existing flexible
and composable data services, seamlessly exploiting and federating
IaaS/PaaS/SaaS resources across different Cloud and Edge environments. We
describe the MEDAL Platform as a usable tool for Data Scientists and Engineers,
encompassing our concept and we illustrate its application though a connected
cars use case.
