Big data is one of the impacts of information revolution due to technological advancements such as communication, mobile and cloud services. The uncontrolled accumulation of structured and unstructured enormous volumes of data creates challenges in storing and manipulating data and obtaining valuable insights from these data. Big Data Analytics is progressively becoming popular and the organizations are in forefront to devise and adopt diversified approaches including machine learning for Big Data Analytics. Business organizations are using data learning as a scientific method for dealing with big data. The use of appropriate data analytics tools is crucial for the organizations to withstand in their business, to face the challenges in the market and gain out of competitive advantage. By considering the overwhelming demand on the data analytics tools, this review paper presents the comprehensive view on various Big Data Analytics methods in place and the state-of-the-art approaches towards Big Data Analytics. This paper also presents upcoming challenges towards big data and suggests certain mechanisms to thwart those challenges.

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Now-a-days, securing data is a typical scenario and secure world is inviting hackers proportional to the technology. Thus, Security must be provided to data in all sides by encoding data at sender and releasing in to network, on other side at receiver, the data must be decoded with the provided credentials. In the proposed system of this paper, we are introducing binary tree traversals to secure data as a ciphering technique. The data may be extracted from a tree through numerous traversal algorithms.