Data Mining Methods: A Review

Abstract

The Big Data revolution is taking place due to the evolution of technology, where the technology enables firms to gather extremely huge amount of data, disseminating knowledge to their customers, partners, competitors in the marketplace [1]. The deeper we dive into technology, the more we compound the physical with the virtual world having in mind for instance the IoT (Internet of Things) as a network of physical devices connected together and able to exchange data. There are many Big Data platforms a company can choose like Hadoop and Apache Spark to analyze large sets of data.Moreover, many data mining techniques like Classification, Clustering Analysis, Correlation Analysis, Decision Tree Induction, Regression Analysis can be used to identify patterns for knowledge discovery. In this paper, there is an extent review and summary of Big Data Mining techniqueswith the most common data mining algorithms suitable to be used to handle large datasets. The review depicts the general pros and cons of these algorithms and the correspondingappropriate fields that apply, and in general acts as a guideline to data mining researchers to have an outlook on what algorithms to choose based on their needs and based on the given datasets.