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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