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We are overwhelmed with data. The amount of data in the world and in our lives seems ever-increasing—and there’s no end in sight. Omnipresent computers make it too easy to save things that previously we would have trashed. Inexpensive disks and online storage make it too easy to postpone decisions about what to do with all this stuff—we simply get more memory and keep it all. Ubiquitous electronics record our decisions, our choices in the supermarket, our financial habits, our comings and goings.

There is a huge amount of data available in the Information Industry. This data is of no use until it is converted into useful information. It is necessary to analyze this huge amount of data and extract useful information from it.

Data mining is defined as the process of discovering patterns in data(extracting information from huge sets of data). In other words, we can say that data mining is the procedure of mining knowledge from data. The process must be automatic or (more usually) semiautomatic. The patterns discovered must be meaningful in that they lead to some advantage, usually an economic one. The data is invariably present in substantial quantities.

Applications of data mining

Data mining is highly useful in the following domains ?

• Market Analysis
• Fraud Detection
• Customer Retention
• Production Control
• Science Exploration

Apart from these, data mining can also be used in the areas of production control, customer retention, science exploration, sports, astrology, and Internet Web Surf-Aid

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