Page 72 - Demo

%u062c%u0645%u064a%u0639 %u0627%u0644%u062d%u0642%u0648%u0642 %u0645%u062d%u0641%u0648%u0638%u0629 %u0640 %u0627%u0625%u0644%u0639%u062a%u062f%u0627%u0621 %u0639%u0649%u0644 %u062d%u0642 %u0627%u0645%u0644%u0624%u0644%u0641 %u0628%u0627%u0644%u0646%u0633%u062e %u0623%u0648 %u0627%u0644%u0637%u0628%u0627%u0639%u0629 %u064a%u0639%u0631%u0636 %u0641%u0627%u0639%u0644%u0647 %u0644%u0644%u0645%u0633%u0627%u0626%u0644%u0629 %u0627%u0644%u0642%u0627%u0646%u0648%u0646%u064a%u062972computerized search of data for knowledge without preconceived assumptions about what this knowledge might be. Data mining is also defined as the process of quantitative analysis of data that is usually large in size in order to find a logical relationship that summarizes the data in a new way that is useful to the data owner. Data mining usually deals with data that has been obtained for a purpose other than the purpose of data mining (eg a bank's transaction database). When dealing with a large volume of data, important issues arise such as how to clean the data so that the analyzes do not lead us to bad directions and how to analyze the data in a reasonable period of time. Data mining is usually done for the purpose of supporting the organization (eg analyzing current data of consumers of a product in order to anticipate future consumer demands). One of the goals of data mining is also to reduce or compress large amounts of data so that we can express in a simple or simple relationship the entire data.