Algorithms in data science are all the rage today with data scientists. With the right algorithm businesses can get measurable value from the huge volume of data collected. There are several types of algorithms- Regression, Clustering, Decision Tree etc. For this paper we will focus on clustering algorithms which are widely used in sorting and classifying big data. The way data is classified is critical to analysts studying the data to provide insights to business decisions. Every large data set can use clustering algorithms to process a variety of data to produce great results. Algorithms are used in image and data processing, calculations, and automated reasoning. The aim of this paper is to touch upon big data analytics, other authors views on this topic in our literature review section, define cluster analysis, present different clustering methodologies with its advantages and disadvantages, a comparison of different clustering algorithms, and wrap up with findings and discussion from our review papers.

Clustering, data mining, big data analytics

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