Page 27 - DCAP603_DATAWARE_HOUSING_AND_DATAMINING

Unit 2: Data Mining Concept

objectives notes

After studying this unit, you will be able to:

l z Explain data mining concept
l z Describe architecture of data mining
l z Know data mining functionalities

l z Describe data mining system classifications
introduction

This unit provides an introduction to the multidisciplinary field of data mining. It discusses
the evolutionary path of database technology, which led up to the need for data mining, and
the importance of its application potential. The basic architecture of data mining systems is
described, and a brief introduction to the concepts of database systems and data warehouses is
given. A detailed classification of data mining tasks is presented, based on the different kinds
of knowledge to be mined. A classification of data mining systems is presented, and major
challenges in the field are discussed.
With the increased and widespread use of technologies, interest in data mining has increased
rapidly. Companies are now utilized data mining techniques to exam their database looking
for trends, relationships, and outcomes to enhance their overall operations and discover new
patterns that may allow them to better serve their customers. Data mining provides numerous
benefits to businesses, government, society as well as individual persons. However, like many
technologies, there are negative things that caused by data mining such as invasion of privacy
right. In addition, the ethical and global issues regarding the use of data mining will also be
discussed.

2.1 Motivation for Data Mining: Why is it important?

In recent years data mining has attracted a great deal of attention in information industry due
to the wide availability of huge amounts of data and the imminent need for turning such data
into useful information and knowledge. The information and knowledge gained can be used for
applications ranging from business management, production control, and market analysis, to
engineering design and science exploration.
Data mining can be viewed as a result of the natural evolution of information technology.
An evolutionary path has been witnessed in the database industry in the development of the
following functionalities:
1. Data collection and database creation,
2. Data management (including data storage and retrieval, and database transaction
processing), and
3. Data analysis and understanding (involving data warehousing and data mining).
For instance, the early development of data collection and database creation mechanisms served
as a prerequisite for later development of effective mechanisms for data storage and retrieval,
and query and transaction processing. With numerous database systems offering query and
transaction processing as common practice, data analysis and understanding has naturally
become the next target.
By performing data mining, interesting knowledge, regularities, or high-level information can
be extracted from databases and viewed or browsed from different angles. The discovered

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