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Data mining is basically a technique that uses these statistical techniques, along with specially designed software to effective data retrieval and analysis. Data Mining is a process of discovering meaningful new correlations, patterns and trends by sifting through large amounts of data stored in repositories, using statistical, data analysis and mathematical techniques. Data mining is also known as Knowledge Discovery in Databases (KDD). Data mining is the process of automatically searching large volumes of data for patterns. Data is derived from the word datum, being its plural term. Traditional data interpretation tools and statistical techniques like correlation and regression analysis are no longer sufficient for sifting through the enormous quantities of data. Patent analysis and mining in combination with market research and financial assessment can build up a strong competitive environment for the competitors for the industries. Data mining works on the basis of computational techniques from statistics machine learning and pattern recognition. Data mining is the crucial process that helps companies better comprehend their customers. Data mining can be defined as ‘the nontrivial extraction of implicit, previously unknown, and potentially useful information from data’ and also as ‘the science of extracting useful information from large sets or databases’. Data mining is not just a data recovery tool. It is now a reliable decision making tool that is used to make most decisions in the areas of direct marketing, internet e-commerce, customer relationship management, healthcare, the oil and gas industry, scientific tests, genetics, telecommunications, financial services and utilities. Data mining can be personalized as per specific requirements to generate the kind of information that is required for a particular application. Data mining is the process of analyzing, interpreting and reporting useful information from masses of data.

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