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Data warehousing is typically done in concert with
data mining. Data warehousing is the storage of lots
of your company's data. Data mining is taking that
data and trying to learn (or mine) useful information
that is not readily apparent in the hopes of making
good business decisions. Let me give you an example of
what all this means. This example was given to me in
my college days, and it has been passed around to many,
many people.
A supermarket chain decided it wanted to analyze sales
patterns. It kept track of what every single customer
purchased. It took every customer's purchases and
stuffed them into a data warehouse. By mining the
purchase data, the supermarket chain was able to find
out that a high number of people who bought diapers on
a Saturday night also bought beer. Now would you have
known that people who bought beer on a Saturday night
tended to also by diapers? I wouldn't have. But that's
what their data mining told them. So they decided to
test the theory. They started putting diapers on
display next to the beer aisle. Both diaper and beer
sales increased as a result! Through data mining of
data that they had warehoused, they were able to make
a decision which resulted in increased sales. Data
mining has also been used to analyze web surfing
patterns and automobile add-on option sales. Did you
know that a high number of people who purchased a
vehicle with cruise control also got power windows and
power locks? So the car companies started to bundle
all three options. The applications to data mining
(with data warehouses) are endless.
How does this work in Oracle? Oracle is one of the
best databases at handling data warehouses. This is
because of the sheer volume of data becomes immense in
data warehouses and Oracle is good at handling very
large databases. Oracle also has offered improvements
to help data mining go faster. But after that, Oracle
is just a database storing data. It is up to the data
mining tools that make the difference.
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