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Data
mining is the extraction
of hidden predictive information from large databases. |
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It is,
in some ways, an extension of statistics, with a few
artificial intelligence and machine learning twists thrown
in. |
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Like
statistics, data mining is not a business solution, it is
just a technology. |
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It uses
a combination of machine learning, statistical analysis,
modeling techniques and database technology |
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Data
mining finds patterns and subtle relationships in data and
infers rules that allow the prediction of future results |
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Its
typical applications include market segmentation, customer
profiling, fraud detection, evaluation of retail promotions,
and credit risk analysis |
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It is
being used both to increase revenues (through improved
marketing) and to reduce costs (through detecting and
preventing waste and fraud) |
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The
foundations of data mining |
Go top |
The
following is the time line of data mining evolutionary period:
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Evolutionary Step |
Business Question
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Enabling Technologies
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Product Providers
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Characteristics
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Data
Collection
(1960s) |
"What
was my average total revenue over the last five years?"
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Computers, tapes, disks |
IBM, CDC |
Retrospective, static data delivery |
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Data
Access
(1980s) |
"What
were unit sales in New England last March?" |
Relational databases (RDBMS), Structured Query Language
(SQL), ODBC |
Oracle,
Sybase, Informix, IBM, Microsoft |
Retrospective, dynamic data delivery at record level
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Data
Navigation
(1990s) |
"What
were unit sales in New England last March? Drill down to
Boston." |
On-line
analytic processing (OLAP), multidimensional databases, data
warehouses |
Pilot,
IRI, Arbor, Redbrick, Evolutionary Technologies |
Retrospective, dynamic data delivery at multiple levels
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Data
Mining
(2000) |
"What's
likely to happen to Boston unit sales next month? Why?"
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Advanced
algorithms, multiprocessor computers, massive databases
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Lockheed, IBM, SGI, numerous startups (nascent industry)
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Prospective, proactive information delivery |
ref:
http://www.thearling.com/text/dmwhite/dmwhite.htm (October
2008)
Now a days, almost all the organisations have
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Massive
data collection and storage |
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Powerful multiprocessor computers |
All that they need is to discover a suitable data mining algorithm
by which they can offer the Right Person at the Right Time through
the Right Channel. Data miners simply do this for the
organisations.
Note: These diagrams are collected
from internet
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Who mines
their data? |
Go to |
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Government
Organizations |
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Non-Government
Organizations(NGO) |
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Research
Institutions |
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Financial
Institutions |
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Corporations |
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Business
Organizations |
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Hospitals |
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Airlines/Railways/Shipping and other Transport Companies |
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Those other
who keep historical and longitudinal data |
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How
privacy is maintained? |
Go top |
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1. |
To maintain
privacy most commonly used databases are
ORACLE
MS SQL
Sybase
MS Access etc.
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2. |
A Database has
following security feature
Access authentication
User privileges
Encryption
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3. |
With the help
of the database technology an organization can maintain
following three level privacy
Do not allow any data mining of customer's data
Allow data mining for internal use
Allow data mining for both internal and external
uses. |
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How
an organization can be benefited? |
Go top |
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1. |
In modern culture most of the
organizations have
Client information database
Client transaction history
Client's
CIB Information particularly for banks
Client performance information
Detail information on Income and expenditure.
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2. |
No need to spend money to gather information.
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3. |
They can mine into their
existing large database which usually remains idle and may
discover
the unexpected way to minimize expenditure
the tricky way to assess real depositors or good borrower
probabilistic behavior of defaulters
where to give more attention now etc. |
At this moment if
you
apply data mining techniques over your existing database you may have
some tricky answers of the following questions:
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Who should be issued
credit card
·
which client should
be given more credit limit
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which group of
people will be your target to provide the above facilities
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what type of
products should be introduced for what type of customers.
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