A business such as an online store like Amazon can collect user data like name, address, mouse clicks on products, how long users stay on page viewing a particular product, marital status, education and many more.
These data are used by these businesses to drive decision-making that enhances the sale of their goods. For instance, adverts and search alternatives about a particular good can be shown to people who have looked at them before. A newly married or pregnant woman would be shown baby products etc.
It is a computer aided technique of searching and evaluating a bulk of data in order to obtain useful information.
This technique searches through the data to find hidden patterns and uses statistical methods to find relationship among data for finding predictive information and for classification of data.
This is a mixture of different disciplines which include machine learning, statistics and artificial intelligence and also some mathematical methods.
Often the useful information is extracted from enormous database using modeling technique which is used to build a model from instances of the data where the solution is known and later apply this model on the instances where the solution is unknown.
In unsupervised data mining, the data analysis is not done by using modeling technique. In other words the labels are provided in order not draw inferences and prediction from data sets. Example is clustering.
In supervised data mining the model is developed to make inferences and classification. Example is neural networks.
For example data mining is used in Medicine industry to provide more accurate diagnostics and treatments on the basis of patient's medical history , physical examination or different patient tests data.
Data mining also makes it possible to manage health resources more efficiently and cost-effectively by detecting risks, predicting diseases in certain sections of the population or predicting hospitalization duration.
