Data mining is about looking for
patterns in data. In data mining, the data is stored electronically and the
search is automated by a computer. There is a huge amount of data available in
the Information industry. This data is of no use until it is converted into
useful information. It is necessary to analyze this huge amount of data and
extract useful information form it. Extraction of information is not the only
process we need to perform. Data Mining also involves other processes sush as data
cleaning, data integration, data transformation, pattern evaluation and data
presentation. Once all these processes are over, we would be able to use this
information in many applications such as fraud detection, market analysis,
production control, science exploration, e.t.c.
Data
mining is about solving problems by analyzing data already present in
databases. Suppose, to take a well-worn example, the problem is fickle customer
loyalty in a highly competitive marketplace. A database of customer choices, along
with customer profiles, holds the key to this problem. Patterns of behavior of
former customers can be analyzed to identify distinguishing characteristics of
those likely to switch products and those likely to remain loyal. Once such
characteristics are found, they can be put to work to identify present
customers who are likely to jump ship. This group can be targeted for special
treatment, treatment too costly to apply to the customer base as a whole. More positively,
the same techniques can be used to identify customers who might be attracted to
another service the enterprise provides, one they are not presently enjoying,
to target them for special offers that promote this service. In today’s highly
competitive, customer-centered, service-oriented economy, data is the raw
material that fuels business growth—if only it can be mined.
To be more
precise, data mining can also be defined as the process of discovering patterns
in data. The process is usually automatic or semiautomatics. The patterns discovered
must be meaningful in that they lead to some advantage, usually an economic
advantage. The data is invariably present in substantial quantities. The
patterns generated from data minig allow us to make nontrivial predictions on
new data.
