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 on-demand webinar covers the fundamentals of building recommendation engines with Neo4j. We 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.
Joe Depeau
Senior Presales Consultant, Neo4j

Originally from the USA but now living in the UK, Joe has over 20 years of varied experience in the IT industry across a number of domains and specialties. Most recently, Joe has focused on technical pre-sales and solution architecture in the data and analytics space. When not geeking out over data and technology he enjoys camping, tending to his garden and allotment, reading, and playing boardgames and RPGs. He also bakes a mean cheesecake.

Andrew Chumney
Single View Solutions Manager, Pitney Bowes

Andrew Chumney joined Pitney Bowes in May 2017 after a 20-year consulting career where he provided executive leadership in corporate restructuring, turn-around, mergers and acquisitions. His particular area of focus was operational efficiency, business intelligence, large enterprise master data management, technology architecture, marketing and brand development. His major clients have included Department of Defense, DynCorp, Lockheed, U.S. Department of Veterans Affairs, Verizon, ABC Radio Networks, Boeing (Jeppesen), Kaiser Permanente, IHS, Owens & Minor and PetSmart.

Most recently his projects have been focused on data science, data patterns and large enterprise master data management architectures. Andrew’s background in large system development and consulting projects allows him to bring a deep understanding of best practices and methodologies from a broad spectrum of vertical markets; manufacturing, healthcare, telecommunications, professional services and defense related industries.

Kelsey Bieri
Data Governance Analyst, ICC

Kelsey Bieri is a Data Governance Analyst at ICC in the Master Data Management and Data Governance Practice. She has contributed to numerous data governance and data lineage projects in the Banking industry, helping organizations build a better understanding of their data universe. Kelsey holds a degree in Management Information Systems from the College of Business at Ohio University.

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