Big Data, highlighting significant signs in extremely large sets of data
When working with disorganized or apparently unmanageable volumes of data, various mathematical tools are used to highlight relevant signals and signal connections. This is how businesses monitor the consumer behaviour of individuals and groups; health experts keep track of diseases and their causes and spreading trends; and physicists deduce the effects of certain particles from the image data of large colliders. This is what data mining is about.
Part of the methods is built on the perception of homomorphism and homology, the similarity of shapes, and the procedures of statistics and probability theory.