Data Mining

Data mining is the process of exploring large volumes of data mainly concerned with businesses or market trends, in order to analyze them and track interrelationships between data sets and consistent patterns. Making predictions is the prime goal of data mining. There are various methods of data mining such as association, classification, clustering, prediction, sequential patterns and decision tree.

Data mining provides an insight into hidden knowledge in the form of associations, correlations, and trends in the data being analyzed. Data mining is widely used in healthcare, business, medicine, government, insurance, and weather forecast. However, breach of privacy and misuse of information are some of its drawbacks.

Selection of target customers by analysing past patterns through data mining helps marketers promote their products smartly. Retail companies find data mining highly beneficial as it helps them predict what kind of product mix attracts the maximum number of buyers. Banking and financial institutions can greatly benefit from past data of customers by finding out loan repayment behaviour and fake credit reporting cases. Data mining helps government bodies unearth criminal activities by analysis of fraudulent financial transactions.

The purpose of data mining is ethical use of the data to make a well-informed decision-making process. However, there is a risk of some industries getting biased against a set of people with certain characteristics, who appear consistently in certain data trends. Private information such as Social Security Number (SSN) and demographic details has a high risk of being misused if shared without caution.

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