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.
Join us for this webinar where we’ll cover the fundamentals of building recommendation engines with Neo4j. We’ll 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.
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.
Nav Mathur is the Senior Director of Global Solutions at Neo. He is responsible for solutions development and Go-To-Market activities for Solutions. Nav is seasoned in business development and brings over 20+ years of experience in consulting focused on Strategy, Planning and Transformational Business & IT Solutions.
Nav has a Masters degree in Software Engineering from Boston University and a Bachelors degree in Computer Engineering. He has also completed an executive management course from Babson College.
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