Big Data Analysis and Its Security Challenges: Exploring Analytics Methods and Tools for Big Data Analysis

Abstract

“Big Data” provides futuristic techniques and mechanisms to store, distribute, capture, manage and examine petabyte or larger-sized datasets with high-velocity and different shapes. Big data can be structured, unstructured or semi-structured, resulting in inability of ordinary data management methods. Data is produced from various different sources and can arrive in the system at various rates. In order to action these large amounts of data in a reasonable and efficient way, parallelism is used. Big Data is a data whose scale, diversity, and complexity require new architecture, techniques, algorithms, and analytics to manage it and extract value and hidden knowledge from it. Hadoop is the core platform for structuring Big Data, and solves the problem of making it useful for analytics purposes. This paper aims to analyze some of the different analytics methods and tools which can be applied to big data, as well as the opportunities provided by the application of big data analytics in Various decision domains.