Production Ready Graph Data Science: Better Predictions With The Data You Already Have


You’ve probably heard that graphs are a major trend in data science and analytics, and you may have wondered how to translate the buzz into business value. We’ll cover the fundamentals of graph data science: what graphs are, how they can be incorporated into your analytics practice, and how Neo4j’s connected data platform can help you move from proof of concept to production. Learn about world use cases including fraud, recommendations, and supply chain optimization to show how it’s possible to translate state of the science techniques into practical business value across multiple industries and use cases.


Philip is SVP of Products for Neo4j, the company behind the open source Neo4j graph database&data science platform. Philip has a deep understanding of how graphs are used, where the space is going, and what uniquely differentiates graph technologies from others and from each other. With 10+ years as Neo4j’s head of product, he thrives on helping users solve intractable problems using the power of connected context, and offers a uniquely rich perspective on the increasingly popular space that he helped to pioneer and grow. Philip is a contributor to the book Graph Databases, published by O'Reilly Media, and he frequently speaks and writes about the technologies, tools, and techniques for deriving value from data. Prior to Neo4j Philip co-founded a data infrastructure startup, worked as Head of Product for database tooling vendor Embarcadero Technologies, and worked at many global companies as a consultant on large-scale mission-critical data projects.

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