Data Drift - Types, causes and measures.

In most big data analysis applications, data evolve over time and must be analyzed and treated in near real time. Patterns and interactions in such data often change over time, thus, models built for analyzing such data quickly become outdated over time. In machine learning and data mining this phenomenon is referred to as data drift. Data Drift Data drift is a change in the distribution of data over time. In machine learning models, data drift is the change in the distribution of a baseline data set on which the model was trained and the current real-time production data.