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People talking about data mining usually means analyzing vast amounts of information and various data. This information helps organizations solve multiple problems and tasks, predict trends, reduce possible risks and find new opportunities. Data mining involves searching for patterns, relationships, anomalies, and deformations to solve a particular problem. In data mining, helpful information is created or found, which can play an essential role in the search.
Data mining is an exciting and diverse process that includes many components, some of which are even confused with the mining itself. For example, statistics is an essential element of data mining (Lu, 2021). Data mining and machine learning fall into data science, but they have different principles of operation, despite some similarities. Data mining involves several vital steps or stages (Lu, 2021). One can distinguish the search for the necessary information, the preparation of data, the evaluation of information, and the provision of a solution.
The process of data mining provides people with many means of solving problems in the digital age. Information mining has many advantages, among which the following can be distinguished (Lu, 2021). This process helps companies to collect reliable information from a massive amount of data. Data mining is more efficient and cost-effective than other data processing applications. It helps businesses make profitable production and operational adjustments and uses new and outdated systems. Data mining allows companies to make informed decisions and identify credit risks and fraud. In addition to the above, this analysis method allows data processing specialists to easily and quickly analyze massive volumes, initiate automated forecasts of behavior and trends, and detect hidden patterns. Thus, it is possible to conclude that data mining is a convenient and effective way of processing information, which has many advantages.
Reference
Lu, Z. (2021). Research on the application of computer data mining technology in the era of big data. In Journal of Physics: Conference Series (Vol. 1744, No. 4, p. 042118). IOP Publishing.
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