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Wednesday 29 May 2013

Dissertation Series - Data mining Literature Review Summary


Data mining is a widely used technology, often deployed in scenarios where large amounts of data are collected and the analysis of this data is problematic.  The use of data mining allows patterns to be gleaned from data and exploited to further the business/organisation objectives.
Data mining is not an out of the box solution that can be deployed to an organisation without technical intervention, as there are many factors that influence the accuracy and usefulness of the end product produced.  These factors must be considered prior to undertaking a data mining project, as it may be the case that the chances of success are low and as such the end product may result in resources being targeted towards false positives.
There are many software solutions used to implement data mining and modelling techniques that can be used within these packages.  These techniques each mine the data in different ways and as such would be used in the appropriate scenario.
There are some resistances to data mining as a technique, these can in the majority of cases by mitigated or at the very least controlled.  There is a common theme of mutual consent between the subject and the organisation, where both parties receive a benefit (as in the Tesco example) the privacy concerns are generally reduced.  This is separate to any legal issues and past examples have shown that even if an organisation adheres to the law there can be issues (such as expressed in the N2H2 example).

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