Let's starts with the WHY we need to perform Dimensionality Reduction before analyzing data and coming down to some inferences, it is often necessary to visualize the data set, in order to get an idea of it. But, nowadays data sets contain a lot of random variables (also called features) due to which it becomes difficult in visualizing the data set. Sometimes it is even impossible to visualize such high dimensional data as we humans fall astray after we reach a dimension higher than 3. Here is where we come across dimensionality reduction. The process of reducing the number of random variables of the data set under consideration, via obtaining a set of principal variables.