We are going to analyze - live on stage - 5 years of GitHub metadata and 42 TB code stored in it to answer questions like:
How is this run How coding patterns have changed through time. Guiding your project design decisions based on actual usage of your APIs. How to request features based on data. The most effective phrasing to request changes. Effects of social media on a project's popularity. Who starred your project and what other projects interest them. Measuring community health. Running static code analysis at scale. Tabs or spaces?
