Google has made available a BigQuery copy of most open source code shared inGitHub. This allows any interested party to analyze 5 years of GitHub metadataand more than 42 terabytes of code easily. In this session we'll cover how toleverage this data - to understand the community around any language orproject. With this, design requests and decisions can be made looking at theactual patterns discoverable through analytical methods. Google has made available a BigQuery copy of most open source code shared inGitHub. This allows any interested party to analyze 5 years of GitHub metadataand more than 42 terabytes of code easily. In this session we'll cover how toleverage this data - to understand the community around any language orproject. With this, design requests and decisions can be made looking at theactual patterns discoverable through analytical methods. During a lighting talk we can quickly see: * 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.