Implication of Mathematics in Data Science Technology Disciplines

Abstract

Mathematics has gained greater significance in the field of data science technology, which incorporates various disciplines-for example, data engineering, data preparation, data mining, predictive analytic, machine learning, and data visualization, as well as statistics. Every modern technology in the present era is tied to mathematics, either directly or indirectly, in order to provide smart and simple answers to problems. The extent to which mathematics has been used varies according to the discipline. Any problem-solving computational paradigm focuses on two basic operations: data storage and data processing. In the field of computational science and technology, mathematical modelling has aided in the development of several computational models for a range of issues. Data Science has recently stepped up to meet the challenges of hundreds of new business-oriented concerns focusing solely on data analysis, one of many recognized problems in computer science. This paper represents the phenomena related to a few mathematical techniques and discusses the significance of these techniques in the contemporary discipline of Data Science.