The document discusses three types of experiences that converge from data: sense, reflect, and do. Sense involves perceiving real-time data from sensors. Reflect involves stepping back and putting patterns into perspective. Do involves enhanced or coached action from data analytics. Examples are given of visualizing invisible patterns from location or taxi traffic data over time. The role of context like time, season, and activity are discussed as important external factors not fully considered in current experiences. A caution is also raised that correlation does not necessarily imply causation from data.