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|Mr Johann Nell|
|Ms Kerry Smith|
Data mining is the process of identifying the relationships and characteristics of a data set, such as cause and effect and correlations. The process often starts by finding natural segmentations in data where logical groupings appear. Those groups can then be classified into segments that have significance to a business.
There are many different approaches for data mining, but most rely on advanced statistical methods like linear and non-linear regression techniques. While these techniques are important, they do not always identify all the salient features of the data, and are particularly inefficient on data sets that are sparse or driven by unknown causal factors. Some well-known non-statistical methods include decision trees and neural networks, which is a technique developed from computational modelling of human brains.
SolveIT Software employs both traditional methods of data mining as well as more advanced, non-traditional methods that are particularly suited to finding difficult, non-linear relationships in data. We employ a world-class team of data miners, which have expertise in most current data mining tools on the market, as well as proprietary SolveIT Software tools that allow for better and more powerful models to be created.
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