Page 138 - DCAP208_Management Support Systems

Unit 9: Data Mining

Like the term artificial intelligence, data mining is an umbrella term that can be applied to a Notes
number of varying activities. In the corporate world, data mining is used most frequently to
determine the direction of trends and predict the future. It is employed to build models and
decision support systems that give people information they can use. Data mining takes a frontline
role in the battle against terrorism. It was supposedly used to determine the leader of the 9/11
attacks.
Data miners are statisticians who use techniques with names like near-neighbor models,
k-means clustering, holdout method, k-fold cross validation, the leave-one-out method, and so
on. Regression techniques are used to subtract irrelevant patterns, leaving only useful
information. The term Bayesian is seen frequently in the field, referring to a class of inference
techniques that predict the likelihood of future events by combining prior probabilities and
probabilities based on conditional events.

Notes Spam filtering is arguably a form of data mining, which automatically brings
relevant messages to the surface from a chaotic sea of phishing attempts and Viagra
pitches.
Decision trees are used to filter mountains of data. In a decision tree, all data passes through an
entrance node, where it faces a filter that separates the data into streams depending on its
characteristics.

Example: Data about consumer behavior is likely to be filtered based on demographic
factors.

Data mining is not primarily about fancy graphs and visualization techniques, but it does
employ them to show what it has found. It is known that we can absorb more statistical information
visually than verbally and this format for presentation can be very persuasive and powerful if
used in the right context.

As our civilization becomes increasingly data-saturated and sensors are distributed en masse
into our local environments, we will inadvertently discover things that might be missed on the
first pass over. Data mining will let us correct these mistakes and discover new insights based on
past data, giving us more bang for our data storage buck.

9.1.1 Types of Information

We have been collecting a myriad of data, from simple numerical measurements and text
documents, to more complex information such as spatial data, multimedia channels, and hypertext
documents. Here is a non-exclusive list of a variety of information collected in digital form in
databases and in flat files.
Business transactions: Every transaction in the business industry is (often) “memorized”
for perpetuity. Such transactions are usually time related and can be inter-business deals
such as purchases, exchanges, banking, stock, etc., or intra-business operations such as
management of in-house wares and assets. Large department stores, for example, thanks
to the widespread use of bar codes, store millions of transactions daily representing often
terabytes of data. Storage space is not the major problem, as the price of hard disks is
continuously dropping, but the effective use of the data in a reasonable time frame for
competitive decision-making is definitely the most important problem to solve for
businesses that struggle to survive in a highly competitive world.

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