Data Mining and Data, Information, Knowledge

Throughout my Computer Science courses, I strive to teach the difference between data and information.

Information is what the user wanted when he ask for the data.

Seldom does an end user want reems of data or Excel spreadsheets hundreds and thousands of rows long. The use needs a discernable, digestable presentation so that he may cognatively absorb the concept being presented.

Should your supervisor ask for the 3rd quarter sales data in the mid-west, do not unload a truckload of sales reciepts on his desk. He is looking for presentations that represents the significance of the data.

But Information is not the end of the story either. An excellent article by Gene Bellinger, et. al. extends the concept of Data --> Information to be
Data --> Information --> Knowledge --> Understanding --> Wisdom
(http://www.systems-thinking.org/dikw/dikw.htm)

Presenting Data as Information has long been the objective of spreadsheets, reports, and even three-dimensional presentations. But moving from Information to Knowledge has been a little more challenging.

Data Mining is a tool to move the to this next level. A great overview of this is provided by Bill Palace at http://www.anderson.ucla.edu/faculty/jason.frand/teacher/technologies/palace/datamining.htm

But Data Mining has advanced past Knowledge into Understanding through the advancement of 'semantics'. (Often referred to as the Semantic Web.) The Wikipedia article provides good coverage on this topic. http://en.wikipedia.org/wiki/Semantic_Web.