Big Data Meets IoT: Lessons From the Cloud on Polling, Collecting, and Analyzing - StampedeCon 2016

This document summarizes Ryan Kirk's presentation at StampedeCon 2016 about predicting outcomes in cloud IoT environments. The presentation covers IoT and cloud computing landscapes, challenges with prediction in different business domains, and lessons learned from data science projects. It discusses stages of a prediction lifecycle model and how different domains like business, engineering and research are involved in each stage. Key challenges and solutions addressed include developing a domain model, approaches for handling variability and uncertainty, techniques for anomaly detection, and the importance of feedback loops and training data evaluation.