How to Build Smarter Recommendation Engines with a Graph Database

Presented by

Joe Depeau, Neo4j

About this talk

Real-time recommendations are at the core of digital transformation in any business today. Whether you’re building features such as product, content or promotion recommendations, personalised customer experience, or re-imagining your supply chain to meet growing customer demands, you’re facing challenges that require the ability to leverage connections from many different data sources, in real-time. There’s no better technology to meet these challenges than a native graph database technology such as Neo4j. This webinar will cover the fundamentals of building recommendation engines with a graph database. We will discuss typical architectures, give a demonstration of Neo4j in action, and go over some of our top use cases of recommendation engines for companies such as Walmart, eBay, and more.

Related topics:

More from this channel

Upcoming talks (0)
On-demand talks (10)
Subscribers (855)
Today’s businesses need to generate real-time, valuable insights from their existing data. In this case, the relationships between data points matter more than the individual points themselves. Industry leads are turning to graph databases which treat those valuable relationships (connections) as first-class entities. Neo4j is the world's leading graph database, with native graph storage and processing.