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What is Data Dredging?

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Data dredging is the automated statistical analysis of large sets of data.
This is similar to data mining with the key difference being that data mining starts with a hypothesis, or something that you expect to find in the data. Data dredging is an automated search for statistical patterns that doesn't start with a hypothesis.
Data dredging tests large sets of data against known statistical models to generate matches. As such, it runs a risk of finding coincidental patterns in data that have no real meaning. In other words, it is a process of finding a pattern that fits the data rather than confirming a pattern with data. As such, data dredging is associated with ethical issues because it's an easy way to create a research paper that looks valid but is essentially auto generated. Nevertheless, the technique does have potential to discover patterns in data that have meaning.
Overview: Data Dredging
An automated search for statistical patterns in data.
Pattern discovery as a starting point of analysis.
Data Dredging tends to produce patterns that exist by chance that have no meaning. In other words, results may lack significance.
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