What is data mining ?
The concept of data mining is when relevant information is depicted from a large corpus of data and is then used to formulate a conclusion. However, in defining the complexity of the process can be differentiated. One can organise data into tables and charts and from there interpret their own conclusion based on a pattern drawn from the information given. This is feasible with small amounts of data, yet when dealing with Big Data, reams of data sets are too complex for just one person to analyse. Therefore, data mining accomplishes this by using algorithms to find a consistency and compare it to inconsistent data. This is done in many marketing companies, usually to make a prediction.[1] In addition, data mining includes databases that are unapparent to the user who uses them because they provide a larger variety of information. When variables are associated with each other, predictions can be made which can either surprise and disagree with the user or confirm their theory. Data mining can form different links between different variables and implementing some of these is risky because the user does not know the solution that the data mining process has concluded. The data is presented in different ways and visual data is a key part of that. This aids the user in understanding the relations more coherently. Data mining consist of many tools which analyse information from different perspectives. It is used in particular to compress large databases which span across different fields.[2] They process data in order to make it useable.
[1]Data mining techniques, http://www.obgyn.cam.ac.uk/cam-only/statsbook/stdatmin.html; consulted 15 April 2012
[2] Data Mining: What is Data Mining?, http://www.anderson.ucla.edu/faculty/jason.frand/teacher/technologies/palace/datamining.htm; consulted 14 April 2012