Data Lineage (DL) has been (re)discovered by many companies because of the GDPR enforcement in May 2018. It is the easiest way to know and keep control on “who can access what, how and why” throughout a corporate analytical platform. The challenge of DL is the non-linear aspect of most data flows, often being M-to-N relationships, making them difficult to analyze easily and quickly with traditional tools. A Graph Database is the perfect way to store and analyze metadata collected for DL because of its modular structure composed of nodes and edges. We will demonstrate an implementation and analysis of DL: generating and loading the graph into the Oracle Database, analyze it via SQL, Notebook (Python/Java) or visually with Cytoscape.