The process of translating data between different database models, such as relational databases to graph databases, requires a nuanced approach that takes into account the distinctive origins and vocabularies of each language family. Unlike simple translations between languages with similar roots, ETL tools must adapt to convert complex data structures and relationships found in relational databases into the more efficient and connected graph database model. With powerful graph ETL tools, this process can be made straightforward by extracting tables and foreign keys, transforming them into nodes and relationships, and loading those elements into a graph database, often uncovering important concepts or entities that were hidden in the original data.