The amount of data collected across various sources in real life situations is never in its complete form. That is, it is never precise or it never gives definite knowledge. It always contains uncertainty and vagueness. Therefore, most of our traditional tools for formal modelling, reasoning and computing can not handle efficiently. Therefore, it is very challenging to organize this data in formal system which provides information in more relevant, useful, and structured manner. There are many techniques available for knowledge extraction form this high dimensional data. This chapter discusses various rough computing based knowledge extraction techniques to obtain meaningful knowledge from large amount of data. A real life example is provided to show the viability of the proposed research.