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In the recent years, there has been an explosion of data and it continues to grow by the second. In fact, data generated in the past decade is much larger than all data collected in the past century combined \cite{data2013}. This enables scientists to get a deeper understanding of the data that was not possible before. But the huge amount of data being collected also poses a bunch of new problems. Data is growing faster than manufacturers can build computers that can process them \cite{chips2016}. Traditional techniques for data analytics are not capable of analyzing these huge amounts of data due to their processing time increasing exponentially as the number of data increases. To make matters more challenging, this is usually coupled with high dimensionality thus, increasing the complexity of the problem further. \cite{xu2016exploring}  No algorithm exists yet that tackles all the problems of handling big data but there has been many works that address some aspects of it. I am particularly interested in pursuing further research on visualizing big data. Visualizing data helps reveal interesting patterns from large data sets that might not be obvious in some representations. It also aids domain experts in extracting information, generating ideas, and formulating hypotheses from the data. However visualizing big and high dimensional data is challenging due to the human limitation of only being able to visualize up to three dimensions.