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Data mining is the practice of automatically searching large stores of data to discover patterns and trends that go beyond simple analysis. Data mining uses sophisticated mathematical algorithms to segment the data and evaluate the probability of future events.
The term "data mining" is a misnomer, because the goal is the extraction of patterns and knowledge from large amounts of data, not the extraction (mining) of data itself.
And Data Matching? Basically it is the ability to identify duplicates in large data sets. These duplicates could be people with multiple entries in one or many databases. It could also be duplicate items, of any description, in stock systems. Data Matching allows you to identify duplicates, or possible duplicates, and then allows you to take actions such as merging the two identical or similar entries into one. It also allows you to identify non-duplicates, which can be equally important to identify, because you want to know that two similar things are definitely not the same.
The key properties of data mining are:
Automatic discovery of patterns
Prediction of likely outcomes
Creation of actionable information
Focus on large data sets and databases
https://docs.oracle.com/cd/B28359_01/datamine.111/b28129/process.htm#CHDFJEJI
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