Data mining is the term used for analysing large sets of data in order to identify trends and patterns. One large volumes of data are collected for the purpose of data mining, we often refer to this as big data. The reason for the term big data is that the data collected and analysed often spans many thousands of records in order to provide more accurate statistics.
It is important to differentiate between what is data mining and what is big data. The term big data refers to the collection of the data itself and often needs specialist software to analyse the data collected as the volume is so large, hence the name. Data mining makes use of artificial intelligence in order to extract relevant information from large sets of data and can create predictions based upon statistics.
Data mining is used throughout a variety of organisations and for several purposes. A useful example of data mining is seen in supermarkets where loyalty cards are introduced, and points or vouchers are provided do the customer in exchange for the supermarket collecting data about their shopping habits.
In general, the data collected as part of data mining is anonymous as the purpose is not to track a particular user but instead to identify the actions, or potential actions of a demographic of either users or customers.
Another example of the use of data mining within the scientific community is within healthcare where patience agrees for anonymous data about their conditions and treatment to be added to a database. This data can then be analysed to identify patterns highlighting the most effective treatments or investigations, helping to improve the treatment for future patience.
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