Streaming data lets us examine business data as either streams or tables, but the connections between the data points add much more value to our data. For this, we need to look at streaming data as a graph. Key use cases include financial fraud investigations, social media analyses, network & IT management, recommendation engines, and knowledge management. In this online talk, we will discuss and demo interactions between streams, graphs and tables with KSQL, Cypher, GraphQL, Neo4j graph algorithms and Confluent Platform. We will walk through the global bank use case and how they are detecting fraud in real-time using graph analytics and event streaming.

Jeff Bean
Confluent Partner Technical Lead

Jeff Bean is a Partner Solutions Architect at Confluent responsible for supporting Confluent partners through the Confluent Verified Integrations Program and evangelizing partner solutions that jointly benefit customers.

David Allen
Partner Solution Architect, Neo4j

David is a deeply technical generalist with experience in managing teams and driving towards complex goals. He has the most fun at work when he is learning something new, or trying to figure out how to do something that hasn’t been done before. When not trying to improve something technical, you can usually find David playing guitar or cycling. He loves meeting new people, and has a very keen interest in language and culture and loves to find common ground with other people through travel and music.

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