Visualizing airport delay correlations with Google BigQuery and Maps API

Josh Livni, from the Maps Developer Relations Team at Google, discusses how Google BigQuery and the Google Maps JavaScript API can be used together to visualize airport delay correlations. By analyzing over 70 million flight records, the team was able to utilize Pearson correlation analysis in BigQuery to predict airport delays based on departure times. However, to better understand the spatial relationships between airports, Livni created a visualization tool using the Maps API. This tool allows users to select an airport and view which other airports are correlated in terms of predicting delays, taking into account different seasonal variations. The process involved creating a JSON dump of the correlations and using a modified earthquake visualization template to map the data, with interactive features that highlight correlated airports when an airport marker is clicked. Livni emphasizes the ease of running complex correlations using BigQuery and the added value of mapping visuals for spatial data analysis.