An overview on big data and machine learning techniques: an introduction to performance management

An overview on big data and machine learning techniques: an introduction to performance management

The rapid growth of data prompts big data to emerge as a new research area that has gained much attention in comparison with recent past. By fast pace of technology we are witnessing great production of data in wide range of science. Thus, such novel conditions imposed by big data reveal serious challenges at different data manipulation levels while reaching high levels of performance. Analyzing this huge volume of various data being generated rapidly, considering its veracity, is not easily available; in the case that traditional data analysis techniques may not be able to tackle such a huge complex amount of data in all situations, some new techniques of big data analytics are designed. In response to these difficulties, new approaches of big data analysis mostly rooted in traditional ones consider the variability and complexity of data stored in proper format of big data. The current research after introducing this newly born technology and the recently developed techniques of big data analyzing studies the related challenges in this field. Particularly, clustering approaches, as one of the most effective steps in machine learning, are widely applied to big data analysis process. After a deeply valuable discussion on the issue, further research directions of big data clustering are presented.