Much like the way a prospector would sift through dirt to find nuggets of gold, data mining is the process of sifting through large sets of data to find pertinent information that could be used for a specific purpose. As a sub-discipline of computer science, data mining is essentially all about patterns.
Once data has been harvested and stored, the next step focuses on making sense of the data — otherwise, it's all meaningless.
Data analysis is carried out in a number of ways, including using concepts like machine learning, where complex adaptive algorithms are used to artificially analyze the data.
More traditional methods involve data scientists — experts trained specifically to make sense of complex information — producing reports for management to act on.
In its safe, legal form, data mining is widespread and used by a large range of industries, from finance to retail.
When browsing the internet, user data is recorded based on websites that are visited, searches that are made, personal details that are entered, and products that are explored.
That data — created by millions of users — can then be examined at a granular level by companies who use it to make informed operating and marketing decisions.
Data mining is used for many purposes, depending on the company and its needs. Here are some possible uses