Data mining is a process which consists of discovering knowledge and patterns in a large group of data. Data mining is a sub-area of computer science and has as main goal to get information from a data set and transform data into a comprehensible structure.
The term ‘data mining’ can be used both as a misnomer and buzzword. Firstly, data mining is a misnomer as the process main goal is the extraction of patterns from a group of data, not the data itself. Secondly, it is a buzzword as the term is applied to large-scale data as well as any application of computer decision support system.
Nowadays, the process of data mining consists of a semi-automatic or automatic analysis of a large amount of information which was previously unknown. The results of this analysis can be used for further studies, as well as in machine learning and predictive analytics.
Data mining belongs to the knowledge discovery in database (KDD) process which is divided into five stages: selection, preprocessing, transformation, data mining, and interpretation and evaluation.
Additionally, the data mining process involves six classes of tasks which are anomaly detection, association rule learning, clustering, classification, regression and summarization.
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