Real-Time Big Data Analytics Perspective on Applications, Frameworks and Challenges

Abstract

The rapid and tremendous growth of data and its diverse resources has become a hallmark of our age, many applications in various fields demand to discover patterns and relationships in real-time to gain awareness of the situation, improve workflows and enhance the bottom line to provide the best insights and make the most appropriate decisions. This requires tools and techniques different from the traditional one by its capability for processing and analyzing these data with its all heterogeneity, complexity, randomness in addition to its huge volume with low latency. Dealing with Big data in real-time poses many challenges in terms of collecting, processing, analyzing the data, and choosing the appropriate framework and architecture to implement the application. The paper reviews different fields of application that require real-time analytics for Big Data with its different approaches and the frameworks used as well as the challenges that may pose for implementing these applications. This review provides a guide for researchers in the future to find out the appropriate study in a specific field of application and the Big Data tools used.