Uncertain information occurs in many vital applications, such as multimedia databases for storing the results of image recognition, logistics databases, stock market prediction software. Different techniques have been proposed to represent and handle uncertain information including a database framework, which is specifically developed to efficiently perform query operations, store such large databases efficiently and most importantly helping mankind solve problems and challenges with uncertain information. We come across several situations in our day to day life, where we unknowingly deal with uncertainty like stock market prediction, image recognition, logistic databases, risk analysis in the healthcare industry, results of a political election and several others. In this thesis, we are considering a very interesting example of finding the next Earth-like planet within our Milky way galaxy or in one of million other galaxies based on the method of discovery, composition, and various other essential parameters. Any astronomy enthusiast would tacitly understand the importance of this question of finding our next home in this vast space consisting of tons of galaxies, which in turn consists of several billions of stars and each star having its own solar system! That indeed is a big question and in this thesis, we employee probabilistic database framework and data analytics using machine learning approach to help find an answer to this question.