1. Big Data and Artificial Intelligence Methods

Since the 1970s, advances in instrumentation and computing have generated ever-increasing amounts of data in ever-shorter periods of time. This data is diverse, whether organized or not, and characterizes one or more “events” (the concept of random variables). Interpreting this data therefore requires the use of powerful mathematical tools to, for example, identify trends, patterns, connections, or correlations. To do this, numerous methods exist: statistical tools, probabilistic models, etc. In all cases, applying these methods requires taking precautions to ensure that data analysis is effective and relevant. This section therefore presents the key characteristics of the data, the methods to apply depending on the objectives, and the precautions to take.