A Brief review on mathematical methods for big data analysis

Mathematicians, computer scientists, and business executives are very enthusiastic about the fast expansion of big data research.The lack of a strong mathematical foundation is still a significant worry despite this growing interest, particularly in light of the extensive marketing and commercialization of big data concepts.By putting forth a mathematical framework that can function as a fundamental theory for big data research, this paper seeks to overcome this difficulty.Specifically, the paper presents the concept of "big" as a mathematical operator.This interpretation makes sense and is consistent with the idea of a linguistic variable, which has been extensively researched for many years in the field of fuzzy logic.This interpretation fits logically.Mathematicians, computer scientists, and business executives are very enthusiastic about the fast expansion of big data research.The lack of a strong mathematical foundation is still a significant worry despite this growing interest, particularly in light of the extensive marketing and commercialization of big data concepts.By putting forth a mathematical framework that can function as a fundamental theory for big data research, this paper seeks to overcome this difficulty.Specifically, the paper presents the concept of "big" as a mathematical operator.This interpretation makes sense and is consistent with the idea of a linguistic variable, which has been extensively researched for many years in the field of fuzzy logic.This interpretation fits logically and naturally with the concept of a linguistic variable, which has been widely studied in the fuzzy logic research community for many years.Adopting such a mathematical model allows big data to be viewed as an abstraction of the technologies, systems, and tools used for data storage, management, and processing that convert traditional data into big data.Furthermore, the notion of infinity in big data is explained through principles derived from calculus and set theory, while the relative nature of big data is understood using operations from fuzzy subset theory.The approach proposed in this paper is expected to support and expand future research and development in areas such as big data analytics, business analytics, big data intelligence, big data computing, and big data science.