Data mining is the process of using sophisticated statistical techniques to extract and analyze data from large databases to discern patterns and trends that were not previously known. The patterns we find are correlations, but not necessarily causation.
Every time we see a link between the occurrence of one event or action with another, we generally assume that one event or action caused the other. But simply linking one occurrence with another does not always prove that the result has been caused by the other.
For example, such data mining might suggest the following relationship between arcade revenue and computer science doctorates awarded in the United States, with a correlation of 0.985.

Total revenue generated by arcades
correlates with
Computer science doctorates awarded in the United States
Correlation: .% (r = .)

a. Is this simply a correlation? Or is there a possibility that computer science doctorates affect total revenue generated by arcades or vice versa? Explain your answer.

Number of people who drowned by falling into a pool
correlates with
Films Nicolas Cage appeared in
Correlation: .% (r = .)

b. Is this simply a correlation? Or is there a possibility that the number of people who drowned was affected by the films Nicolas Cage appeared in? Explain your answer.

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2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 $2 billion 2000 degrees 1500 degrees $1.5 billion 1000 degrees 500 degrees $1 billion 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 Arcade revenue Computer science doctorates Arcade revenue Computer science doctorates 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 140 drownings L 16 films 120 drownings 4 films 100 drownings 2 films O films 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 80 drownings + Nicholas Cage + Swimming pool drownings Swimming pool drownings Nicholas Cage