Customer Behaviour Analytics: Billions of Events to one Customer-Product Property Graph

Data Science, Tools & Technology
Location: King's Suite - Sandringham Level: Intermediate
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Graphs, the data structure, can be used to represent data to bring meaning to massive amount of data. In fact, when viewed in a graphical manner, some problems are naturally easier to solve. One example is customer behaviour analytics. Finding out what differentiate people that viewed item A and purchased A versus those that viewed item A and purchased B is essentially a graphical traversal problem through behavioural relations between people and products.

On the other hand, data are typically generated from events as dimensionless data points. Thus, the technical challenge discussed in this talk is transforming flat data into linked data. Yet, even more exciting is demonstrating the business value by enabling natural customer behavioural querying with limitless data dimensions.

Photo of Paul Lam

Paul Lam


Paul Lam is a data scientist at uSwitch based in London. He spends most of his time extracting features from messy data on scale or building data workflows to make data useful and accessible for the business. Paul is also a core committer on an open source MapReduce tool called Cascalog written in Clojure.


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