Top 10 Use Cases: Data Lineage

Graph databases are being used by financial institutions to solve their extensive data lineage challenges, which require tracking data connections across complex networks of investments and holdings. These organizations face stringent requirements, such as BCBS 239, that demand flexibility and persistence in tracing data dependencies through multiple data silos. Graph technology offers a single source of truth, revealing complex or hidden data connections within milliseconds, and can integrate information into a single, enterprise-wide logical data model. A real-world example is UBS, which used Neo4j's graph database to solve its data lineage challenges by modeling their data and providing governance over data movement, enabling consumers to understand the datasets they offer and how they relate to others. This approach offers beneficial outcomes such as tracing risk factors back to original data sources, spanning multiple data silos into a unified dataset, and handling mergers and reorganizations that affect trading desks.

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