ICT plays an indispensable role in the overall development of rural areas, especially in developing economies. There is an urgent need to bring the rural areas into the mainstream by providing them the research and findings which until now only the top level planners to some extent are using. The analysis of the Resource envelops of various department shows the gaps where a planner can pay attention and thus minimize the disparity of allocation. Outlier detection is a primary step in many data-mining applications. Outlier detection for data mining is often based on distance measures, clustering and spatial methods. In many data analysis tasks a large number of variables are being recorded or sampled. One of the first steps towards obtaining a coherent analysis is the detection of outlaying observations. Although outliers are often considered as an error or noise, they may carry important information. Detected outliers are candidates for aberrant data that may otherwise adversely lead to model misspecification, biased parameter estimation and incorrect results. It is therefore important to identify them prior to modeling and analysis.