In this paper discuss about classifying and analysis of Big Data using Neural Fuzzy Systems. A Neuro-fuzzy system is a fuzzy system that uses a learning algorithm derived from or inspired by neural network theory to determine its parameters (fuzzy sets and fuzzy rules) by processing data samples. A Neuro-fuzzy system can be viewed as a 3-layer feed forward neural network. The first layer represents input variables, the middle (hidden) layer represents fuzzy rules and the third layer represents output variables. The input variables are Big Data (term for Data sets). The middle or hidden layer is used to generate an automatic rule for structured and unstructured data by learning algorithm. In third layer it generates an output. Finally analyse latency, throughput, and fault rate.