This document summarizes a project conducted by SITA Lab at Sydney Airport to analyze big data and predict passenger flows. It describes how they used WiFi analytics, flight schedules, FIDS data, and immigration data to predict arrivals flows and provide recommendations. Key learnings included focusing on business intelligence objectives rather than just analyzing data, using commodity cloud servers and open source software to start small, and prioritizing learning over specialized hardware or experts. The goal of telling stakeholders something new about passenger flows that they did not already know from this big data analysis was achieved.