Our Journey to Self-Discovery: Synthesizing 30 Years of Data Pipelines With Knowledge Graphs

Mayank Gupta, Senior Vice President of Technology at LPL Financial, discussed how his company uses knowledge graphs to overcome FinServ data challenges. He shared his journey with graph databases, starting from his early days with Neo4j, and how it has evolved over the years. LPL Financial's use cases for knowledge graphs include solving complex data modeling problems, improving surveillance and detecting suspicious activity, and enhancing financial concepts and health documents. Gupta highlighted the importance of relationships in FinServ data and how graph databases can surface them. He also discussed the challenges of scaling and integrating data pipelines, which knowledge graphs can help address. The interview emphasized the benefits of knowledge graphs for self-discovery, transparency, and enabling business leaders to make informed decisions. Future trends include ubiquitous computing, where graph technology will play a key role in driving interfaces and analytics, and changing operating models underpinned by these graphs.

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