  Big data is gaining overwhelming attention since the last decade. Almost all
the fields of science and technology have experienced a considerable impact
from it. The cloud computing paradigm has been targeted for big data processing
and mining in a more efficient manner using the plethora of resources available
from computing nodes to efficient storage. Cloud data mining introduces the
concept of performing data mining and analytics of huge data in the cloud
availing the cloud resources. But can we do better? Yes, of course! The main
contribution of this chapter is the identification of four game-changing
technologies for the acceleration of computing and analysis of data mining
tasks in the cloud. Graphics Processing Units can be used to further accelerate
the mining or analytic process, which is called GPU accelerated analytics.
Further, Approximate Computing can also be introduced in big data analytics for
bringing efficacy in the process by reducing time and energy and hence
facilitating greenness in the entire computing process. Quantum Computing is a
paradigm that is gaining pace in recent times which can also facilitate
efficient and fast big data analytics in very little time. We have surveyed
these three technologies and established their importance in big data mining
with a holistic architecture by combining these three game-changers with the
perspective of big data. We have also talked about another future technology,
i.e., Neural Processing Units or Neural accelerators for researchers to explore
the possibilities. A brief explanation of big data and cloud data mining
concepts are also presented here.
