From edge to cloud, big data analytics is growing fast, and its energy consumption has become a reason of concern for national grids and they generate significant carbon emissions. The GLACIATION project aims to address this issue through energy-efficient data operations. By developing a novel Distributed Knowledge Graph (DKG) that stretches across the edge-core-cloud architecture, reduction in the energy consumption for data processing will be achieved through AI enforced minimal data movement operations. GLACIATION will achieve significant power consumption reduction through optimizing the location where analytics are carried out. The projects Meta Data framework will provide tools that incorporate privacy and trust aspects in the data operations. GLACIATION is demonstrated on three relevant industry settings which benefit from optimized data movement and power consumption reduction. More specifically, GLACIATION use cases cover public-service, manufacturing, and enterprise data analytics.