Why use data mining?

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Why use data mining?

Data mining is one of the stages of obtaining information from various databases. Therefore, data mining can be referred to as knowledge acquisition, data mining, or mining. Computer data is used for data mining – we can search hidden data in databases and data warehouses. Why use data mining?

The development of technology causes the accumulation of data – more and more databases and data warehouses are being created. With each passing day, companies, enterprises, state institutions and banks add more data to their resources. Is there really so much data? It is enough to imagine that supermarkets register daily sales of about a thousand or more items. Banks record hundreds of thousands of transactions, and when it comes to online resources, Google’s archive holds at least several billion pages. To make good use of information resources, you need to know how to quickly and effectively acquire relevant knowledge. For this purpose, data mining is also used, otherwise known as knowledge acquisition, data mining or data mining. This means that exploration in this case is discovering the necessary knowledge in databases or data warehouses. One definition characterizes data mining as a technique for automatically discovering schemas, rules and patterns in large data sets. It is a process that meets two conditions: firstly, it is automatic, and secondly, it does not require human supervision. Despite the complexity of the process and huge databases, exploration is an extremely fast solution. It is worth adding that it is also intended to recognize enterprises’ problems, and thus is to help in business. In addition, we call data mining the tool that generates analyzes and reports.

Why use data mining?
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Data mining methods

Data mining methods can be divided in terms of the purpose of exploration and in terms of the types of patterns discovered during data mining. In total, we can distinguish six main classes of data mining: classification, association discovery, grouping, detection of changes and deviations, discovery of singular points and analysis of time courses.

Data mining methods are a tool for discovering unknown knowledge, rules, patterns and relationships in databases or rather data warehouses. Their use can be indicated in all areas in which it is necessary to analyze and evaluate a large amount of data that a person cannot quickly analyze. The success or failure of the analyzed problem and even the entire company may depend on the speed and correctness of the knowledge discovered in databases and its appropriate application. However, it should be remembered that the conclusions obtained from data mining methods were formulated in the form of presumptions, and not in the form of categorical statements. That the knowledge obtained from data mining methods be used prudently in decision-making processes. Not every rule or pattern discovered will be useful. It is the man who must make the final assessment of the knowledge received.

 

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