This document discusses using data and data visualization tools to enable real-time decision making. It describes a continuum from data collection to learning systems. Data collection systems ingest and store data. Visualization systems present data in consumable ways. Recommendation systems suggest actions based on data. Human-directed systems allow defining rules. Learning systems take action based on past behavior. An example of a garden weather station is provided that would collect environmental data, visualize it, send recommendations based on thresholds, use rules, and have a learning component to optimize settings.