Mapping Big Data's 5V Constraints To Machine Learning Architecture And Scalability

Abstract

 The speedily developing field of big data analytics uses machine learning to analyse large and diverse information to help companies make smart business decisions. Analytics of Big data is important for national intelligence, cybersecurity, biology, fraud detection, and medical informatics. The use of massive volumes of data powered the development of big data in the early 2000s. The term "Big Data" refers to data collections of high size, speed, or complexity, making normal processing methods unsatisfactory. Large datasets have important potential, and machine learning powers artificial intelligence to extract information to support informed decision-making. In this article, we discuss machine learning procedures, big data knowledges, and applications of machine learning. This article discusses noteworthy issues with applying machine learning on large datasets.  This research will inspect the current advances and problems at this unique convergence, revealing the potential for transformation in big data processing using machine learning.