Data Mining: What Is It and How Is It Used?

Data mining is a way to gain market intelligence from a huge amount of data . the problem today is not the lack of data, but how to learn from it . in data mining, the data tell the story, but it is up to you how to use that information. Data mining is used to search for valuable information from the mounds of data collected over time, which could be used in decision making. The information may be certain patterns and/or relationships that exist. With data mining, a retail store may find that certain products are sold more in one channel of distribution than in the others; certain products are sold together; certain products aie sold more in one geographical location than in others; and certain products are sold when a certain event occurs. Wal-Mart, for example, has found that the sales of beer increase when a hurricane is imminent. This means that they have to hold more than the usual supply o fbeerwhena hurricane is expected. With data mining, a financial analyst would like to know the characteristics of a company becoming insolvent; human resource managers would like to know the characteristics of a successful prospective employee; credit card departments would like to know whichpotential customers are more likely to pay back the debt and when a credit card is swiped, which transaction is fraudulent and which one is legitimate; direct marketers would like to know which customers purchase which types of products; booksellers like Amazon would like to know which customers purchase which types of books (fiction, detective stories, or any other kind); and so on. With this type of information available, decision makers will make better choices. Human resource people will hire the right individuals. Credit departments will target those prospective customers that are less prone to become delinquent an d'or less likely to involve in fraudulent activities. Direct marketers will target those customers that are more likely to purchase their products. With the insight gained from data mining, businesses may wish to re-configure their product offering and/or emphasize specific features of a product. These are not the only uses of data mining. Police use this tool to determine when and where a crime is likely to occur, and what would be the nature of that crime. Organized stock exchanges detect fraudulent activities with data mining. Pharmaceutical companies mine data to predict the efficacy of compounds as well as to uncover new chemical entities that maybe useful for a particular disease. The airline industry uses it to predict which flights are likely to be delayed (well before the flight is scheduled to depart). Weather analysts determine weather patterns with data mining to predict when there will be rain, sunshine, a hurricane, or snow. Nonprofit companies use data mining to predict the likelihood of individuals making a donation for a certain cause. The uses of data mining are far reaching and its benefits may be quite significant. DATAMININGIN HISTORICAL PERSPECTIVE The job of a data miner is to extract valuable information from the data available. The approach to finding information is to find patterns and relationships present in the data, which, of course, is not new. Indeed, man lias looked for patterns in almost every endeavor undertaken by mankind. Early man looked for patterns in the sky at night, in the movement of stars and planets, and in the weather. Modem man still hunts for patterns in early election returns, in global temperature changes, and in the sales data of new and matured products. Over the last 25 years or so, there has been a gradual evolution from data processing to data mining. In the 1960s, businesses routinely collected data and processed it using database management techniques that allowed an orderly listing and tabulation of the data as well as some query activity. On-line Transaction Processing (OLTP) became routine, data retrieval from stored data became faster and more efficient because of the availability of new and better storage devices, and data processing became quicker and more efficient because of advancements in computer technology. …