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Data mining is usually defined as a nontrivial extraction of implicit, previously unknown and useful information from databases and websites. Generally, the techniques used should ensure that the information extracted is useful, previously unknown and implicit. Data mining is generally a huge industry in many areas other than healthcare and life sciences. This is not to imply that it is not a technology there but it is a relatively a new concept and not mostly used.

The technology is used to enable clients, companies to obtain, generate and use the large quantities of data. Usually, companies rely greatly on data mining for a number of reasons such as marketing, database providers, manufacturing, travel industry, financial and banking services, engineering, and telecommunications among others.

The Common Idea About Data Mining

The common idea about data mining is that all the industries have at their disposal enormous amounts of information. The information can be about their clients or even operations and harvested in different ways. So as to maximize the usefulness of the data, they have incorporated different techniques that drive services such as web scraping, data extraction, web data mining that help them to glean particular trends and patterns from the data and also offering simulations and predictions concerning the future events.

For instance, it is no surprise for a biopharmaceutical industry to regularly employ a number of data mining methodologies that enable it to deal with large amounts of biological data in different forms that have been collected by the industry. From the annotated databases of molecular pathways and disease profiles to structure, sequences, population and individual clinic tests, this industry has inundated with information at its disposal, and data mining becomes the core of advanced methodologies that deal with information overload.

The technology So let’s understand this technology, data mining. It uses a technology known as machine learning and visualization and statistical methodologies in representing and discovering knowledge which is easily understood by humans. The main idea here is to extract, reduce complexity, or mine, useful and relevant information from databases.

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