Databases Reference
In-Depth Information
Knowledge
Figure 1.3
Data mining—searching for knowledge (interesting patterns) in data.
appropriately named “knowledge mining from data,” which is unfortunately somewhat
long. However, the shorter term,
knowledge mining
may not reflect the emphasis on
mining from large amounts of data. Nevertheless, mining is a vivid term characterizing
the process that finds a small set of precious nuggets from a great deal of raw material
(Figure 1.3). Thus, such a misnomer carrying both “data” and “mining” became a pop-
ular choice. In addition, many other terms have a similar meaning to data mining—for
example,
knowledge mining from data
,
knowledge extraction
,
data/pattern analysis
,
data
archaeology
, and
data dredging
.
Many people treat data mining as a synonym for another popularly used term,
knowledge discovery from data
, or
KDD
, while others view data mining as merely an
essential step in the process of knowledge discovery. The knowledge discovery process is
shown in Figure 1.4 as an iterative sequence of the following steps:
1.
Data cleaning
(to remove noise and inconsistent data)
2.
Data integration
(where multiple data sources may be combined)
3
3
A popular trend in the information industry is to perform data cleaning and data integration as a
preprocessing step, where the resulting data are stored in a data warehouse.
