Data Mining
In today’s business world, information about
the customer is a necessity for a
businesses trying to maximize its profits.
A new, and important, tool in gaining
this knowledge is Data Mining. Data
Mining is a set of automated procedures used
to find previously unknown
patterns and relationships in data. These patterns
and relationships, once
extracted, can be used to make valid predictions about
the behavior of the
customer. Data Mining is generally used for four main tasks:
(1) to improve
the process of making new customers and retaining customers; (2)
to reduce
fraud; (3) to identify internal wastefulness and deal with that
wastefulness
in operations, and (4) to chart unexplored areas of the internet
(Cavoukian).
The fulfillment of these tasks can be enhanced if
appropriate data has been
collected and if that data is stored in a data
warehouse. This makes it much
easier and more efficient to run queries over
data that originally came from
different sources." When data about an
organization’s practices is easier
to access, it becomes more economical to
mine. "Without the pool of validated
and scrubbed data that a data warehouse
provides, the data mining process
requires considerable additional effort to
pre-process the data" (SAS
Institute). There are several different types
of models and algorithms used to"mine" the data. These include, but are not
limited to, neural networks,
decision trees, rule induction, boosting, and
genetic algorithms. Data Mining is
largely, if not entirely used for business
purposes. The highest users of data
mining include banking, financial, and
telecommunications industries (Two
Crows). Data mining will have a
different effect on different industries in the
business world. The key to
succeeding in this rapidly changing industry is to
understand the customer,
or the market that the customer represents. Through
data mining, companies
can know what their customers have done in the past and
what they will do in
the future. With this information, the companies will be in
ideal positions
to make business decisions based on the information they have
gained from the
data mining process.