Data Mining, Applications, Requirements, Process and Tools

The emergence of data mining science has made data become one of the most valuable assets of organizations and with the correct use of this trump card, software systems can produce results in a different and effective way. The process of extracting and discovering patterns and correlations from a large volume of raw data from one or more databases is called data mining. Data mining is an important and fundamental part in the analysis of distributed information of today's organizations. The data obtained from data mining can be used in business intelligence and advanced analysis. Increasing capacity, finding hidden patterns, trends and correlations in data sets is one of the main advantages of data mining tools. Due to the evolution of data storage technology and the growth of big data, the use of data mining techniques has increased dramatically in the last two decades. Using the best data mining tools helps businesses to make decisions and implement knowledge-based processes more efficiently by identifying hidden relationships and patterns in the data. Despite the technology constantly evolving to handle large-scale data, leaders still face challenges around scalability and automation. According to the importance of the topic in this article, we are going to examine the applications of data mining, requirements, process and important tools in this field. In the end, we will examine the technological perspective of data mining.