This document discusses real-time big data analytics from deployment to production. It covers: 1) Distilling raw data like log files and sensor streams into structured data using Hadoop for analytics. 2) Developing predictive models using techniques like decision trees, clustering, and ensembles on structured data. 3) Deploying models for real-time scoring via SQL, code, or PMML on either batch lookup tables or streaming data factors. 4) Scoring billions of predictions daily for applications like determining why customers buy products and attributing marketing channels. 5) Regularly refreshing models to incorporate new data and outcomes using techniques like exploratory analysis and time-to-event modeling