Scrutinizing Big Data with Commutative and Non-commutative Algebra

Abstract

A theoretical framework based in commutative and non-commutative algebra of abstract operators, is presented. Basically, attention has been paid on the form as these operators through eigenvalues equations can model time-dependent data. The value of USD dollar against euro has been focused, because its relevance. The 20 -years period data have been used. Data has shown a varied morphology that is seen as a response to economic decisions of countries against global development. This, has suggested to employ different mathematical forms derived from algebras. Thus, when model fits data, one can speak about data is obeying a certain set of algebraic rules that are not visible in first sight. The algebra-based model also might exhibit capabilities as to predict values in a short period within statistical and systematical errors involving the mathematical procedures and approximations.