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The comparison between all these sets of big data analytics is that they capture digital information; hence they all share a similar value of analyzing data for organizations. Descriptive analytics is the first simplest category of big data analytics among predictive and prescriptive analytics. It allows a user to divide data into smaller parts that are highly useful information. The purpose of descriptive analytics is to summarize occurrences, for example, social analytics (Sharda, Delen, Turban, Aronson, and Liang, 2014). Descriptive analytics assess simple event encounters that represent raw data, such as the number of followers or posts on a social media platform. It mainly processes data into results that can be interpreted at a glance without high complexity in data analytics.