Today every second the size of data (real world data) is increasing exponentially. Real world data means digital photographs, speech signals, scientific observations, statistic calculations etc. improvement in technology have also improved data quality and quantity. This improvement also helps in increasing the features or dimensions of observed data. As the dimensions increases the size of data increases. Second, introduction of interdisciplinary fields motivating students from diverse fields to work together and develop new road maps in different research areas this also increase the size of data as the accuracy increases with new mile stones. The challenge is to store data in minimum space and retrieve it adequately and accurately. For minimizing the space reduction of dimensionality is needed. The goal of reduction of dimension is to make low dimension representation of high dimension data so that the structure or geometry of data will be preserved. The dimension of data means the cardinality of variables that are compute on each observation to define this observation uniquely. Reduction of dimensionality helps minimize space, fast information retrieval, image processing, easy visualization, good classification of data set easily etc. Actually reduced dimensional representation should have a dimensionality that consists to intrinsic dimensionality of data. The intrinsic dimensionality means the least number of dimensions used for explanation of the observed properties of the data.