• I. CAROL

In today's world, humans are capable of producing a large amount of raw data which is furthermore considered as Big Data. Big Data requires high-performance hardware and software to process and to produce fruitful information which will be useful to create complex results. Big Data is productively used in the field of business analytics to create rightful insight. It is carried on with many programming languages and tools as well as various Big Data analytical techniques. Big Data analytics is classified into various analytics including predictive analytics which produces prediction based insights. Predictive analytics had been playing a vital role in every aspect of data processing. There are many algorithms such as Clustering, K- means, Classification, Random forest and decision tree which are capable of producing high precision of information. Additionally, this paper proposes a survey on predictive analytics and comparative literature between the Random Forest algorithm and the Decision Tree algorithm

Big Data, Predictive Analytics, Classification, Random forest, and Decision Tree algorithm.

"Comparative Survey of Random Forest and Decision Tree in Predictive Analytics", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 3, page no.a367-a378, March-2022, Available :http://www.jetir.org/papers/JETIR2203045.pdf

"Comparative Survey of Random Forest and Decision Tree in Predictive Analytics", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 3, page no. ppa367-a378, March-2022, Available at : http://www.jetir.org/papers/JETIR2203045.pdf