Data Science and Graphs. Q&A with Ben Squire (Meredith)

Q1. Can you talk about the major differences in the data science projects you work on before using graph databases and after?

Two major differences in data science projects before and after working with graphs databases are in framing the problem statement and new approaches to solutions of the problem.

One clear example can be seen with our work with recommendation engines. Look-a-like modelling and customer segmentation are a major research & development area at Meredith, previously our work focused on web logs at a cookie based level, whereby given a particular action in our web logs, such as signing up for a newsletter or clicking on an advertisement, we would analyze traits of these cookies to find others which had similar interests or reading patterns to present similar offers or ads in order to have a higher click through rate than randomly selected audiences.

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