We started with the goal of developing a predictive model for flight pricing using data feeds from Airline Global Distribution systems, Online Travel Agency feeds, and external behavioral data sets. The implementation is done using a sharded MongoDB cluster for storage and python for computation. We'll discuss hurdles from company size, technical, business, and data perspectives. We'll also step through the strategy we used to take our large data sets and allow our analysts to query it. By the end of the talk, you should know how to normalize multiple large feeds in Mongo and learn from our mistakes.
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