Customer Data Platforms (CDPs) demand more than just relational joins. Modern organizations need to model relationships across channels, devices, and identities. In this session, we’ll show how to build a graph-powered CDP on Databricks using Neo4j. With the Neo4j Spark Connector, we’ll stream multi-channel data into Delta Lake, run graph queries to uncover hidden affinities, and deliver insights back into Databricks ML and BI. We’ll cover real-world use cases like identity resolution, cross-channel attribution, and personalization.

Attendees will leave with code patterns and design approaches to bring graph analytics into their Lakehouse and deliver customer intelligence that traditional CDPs struggle to achieve.