Abstract

The exploration of BIG data is one of the biggest areas in researchers currently present. It is widely accepted that the advent of big data will have far-reaching effects on many fields, including science, commerce, industry, government, society, and so on. Large, complex datasets are being created at an everincreasing rate, making it imperative to develop novel methods for analysing this ‘‘Big Data.’’ Since dealing with Big Data presents significant obstacles for the applications, data mining techniques are proving to be of tremendous assistance in the field of Big Data analytics. Analysing such massive datasets using Big Data analytics allows for valuable insights to be gleaned. All things technological, including social media, financial technology, and scientific data, contribute significantly to the exponential expansion of data in the database in the modern digital era. Data mining is the process of sifting through large amounts of data in search of useful information. As a consequence of this, the R predictive algorithm is an improved measure of the composition of the surrounding air and our Experimental Analysis into the Predictive Capability of the Mathematics Models Algorithm. In this article, we’ll look at some of the most pressing problems brought on by big data, as well as some of the ways in which those problems could be overcome.

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