When I ?rst came across the term data mining and knowledge discovery in
databases, I was excited and curious to ?nd out what it was all about. I
was excited because the term tends to convey a new ?eld that is in the
making. I was curious because I wondered what it was doing that the
other ?elds of research, such as statistics and the broad ?eld of
arti?cial intelligence, were not doing. After reading up on the
literature, I have come to realize that it is not much different from
conventional data analysis. The commonly used de?nition of knowledge
discovery in databases: "the non-trivial process of identifying valid,
novel, potentially useful, and ultimately understandable patterns in
data" is actually in line with the core mission of conventional data
analysis. The process employed by conventional data analysis is by no
means trivial, and the patterns in data to be unraveled have, of course,
to be valid, novel, useful and understandable. Therefore, what is the
commotion all about? Careful scrutiny of the main lines of research in
data mining and knowledge discovery again told me that they are not much
different from that of conventional data analysis. Putting aside data
warehousing and database m- agement aspects, again a main area of
research in conventional database research, the rest of the tasks in
data mining are largely the main concerns of conventional data analysis.
