In this paper, gamma exponentiated distribution has been investigated. Its own complexity as well as rate of failure parameters could take on a variety of different aspects. It includes various relevant distributions identified in the literature as things that made, including that of the gamma as well as exponential distributions. This same exponentiated distribution's flexibility has been assessed by performing everything to various dataset while connecting it to all the other representations. The non-parametric approach can also be used to quantify parameters of the model, and indeed the empirical understanding sequence has been obtained. This same recent model's predictability becomes evidenced by some of its deployment to something like a big data platform.