A Survey on Distributed Frameworks for Machine Learning Based Big Data Analysis

Abstract

The rapid pace of technological progress has led to an increasing growth in the volume of digital data circulating on servers and on the web. This has contributed to the birth of the concept of Big Data. Simply put, this concept refers to the huge amount of information on the Internet; yet it also reveals the heterogeneity and complexity of such data. Therefore, analyzing these data, especially unstructured data, has become important since they can be used in many areas such as company management, health, smart city. In order to analyze these data, novel efficient tools are required as the current ones are not effective enough. This paper surveys the most frequently used tools and platforms for Big Data analysis with due emphasis on Machine Learning-based models. The results of this study provide in-depth knowledge of Big Data analytics applications related to machine learning that can contribute to the innovation and development of big data analytics platforms. Moreover, it helps to choose the right tools to ensure the best performance for designing an analytics system.