Digital twins (DTs) have become increasingly complex as they integrate data from diverse heterogeneous sources, which presents a major challenge in querying and aggregating information in a unified and secure way. The Entity-Relationship Digital Twin (ERDT) model provides a basis for representing both physical entities and their digital counterparts at the conceptual level. This paper extends this modeling solution by proposing a Domain Specific Language to define queries on the DT through ERDT views. This DSL is supported by a code generation strategy that translates the defined queries into executable Python specifications. In addition, we also present a reference architecture for deploying the software artifacts generated from models to obtain a fully operative DT. We validate our approach through the development of a DT for the management of the truck fleet in a real industrial scenario located within the logistics operations of Mercadona, one of Spain’s largest supermarket chains. The results demonstrate that our solution covers data heterogeneity and security constraints while also providing enhanced query capabilities in a production environment.