The growing size of data collected from social networking sites, videos, audios, log files, texts, conversations, documents, medical records, images, tweets, emails, etc have given rise to various issues, the primary being handling such enormous amount of related data while maintaining the time and cost of the operation. This huge amount of data is referred to as Big Data and the task of handling it comes in Big Data Analytics. The various data mining techniques proposed till date serve as an aid to the problem of efficiently analyzing, visualizing and storing Big Data. The K-means clustering algorithm, though proposed more than 50-years ago, serves to be an excellent data mining solution able to cluster this increasing size of data. This paper discusses the various issues encountered in Big Data Analytics over the years and the relevance of the K-means clustering algorithm regarding the same.
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