TRENDS IN DATABASE TECHNOLOGY - Database Design and Development: An Essential Guide for IT Professionals - page 660

OLAP
System

DATA STAGING AREA

Source
Operational
Systems

Flat files
with
extracted
and
transformed
data

Load image
files ready
for loading
the data
warehouse

Enterprise
Data
Warehouse

OPTIONS
FOR DATA
EXTRACTION

Data selected,
extracted,
transformed, and
prepared for mining

Data
Mining

Figure 20-21 Data mining in data warehouse environment.

The data warehouse is a valuable and easily available data source for data mining
operations. Data extractions for data mining tools to work on come from the data
warehouse. Figure 20-21 illustrates how data mining fits in the data warehouse
environment.
Note how the data warehouse environment supports data mining. Note the levels
of data held in the data warehouse and the OLAP system. Also, observe the flow
of data from the data warehouse for the knowledge discovery process.

Major Data Mining Techniques and Applications Figure 20-22 shows examples
of application areas, mining functions, mining processes, and techniques.
Using the figure, try to understand the connections on the basis of the following
remarks:

• Data mining algorithms are part of data mining techniques.
• Data mining techniques are used to carry out the data mining functions. While
performing specific data mining functions, you are involved in getting this done
through mining processes.
• A specific data mining function is generally suitable to a given application area.
• Each of the application areas is a major area in business where data mining is
actively used now.

LEADING TRENDS: BASIC OVERVIEW

In this section, we consider a few leading trends in database technology. This is not
an in-depth coverage of each topic. The intention is just to highlight the main points
and expose you to what is out there and what you should be watching for.