The reason that data alone is not knowledge, but merely data, is it lacks structure, organization, direction, coherence, point or conceptual focus. Just as an interpretation without supporting data would be empty, data without a unifying interpretation is meaningless and leaves the data collector blind. The challenge for the data miner – and what distinguishes the data miner from the data hacker – is to systematically discover and verify meaning amidst apparent disorder and occasionally even chaos.

One important goal of data mining is to discover, define and determine the relationship between variables. These variables, in turn, represent the levers and mechanisms that move business operations. A variety of pitfalls relating to extraneous, hidden and distorter variables can result in misunderstandings and inaccurate conclusions.

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