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 new concept and not mostly used.
The technology is used to enable clients, companies to obtain, generate, and use 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. Data is harvested in different ways. So, to maximize the usefulness of the data, organizations have incorporated different techniques that drive services such as web scraping, data extraction, web data mining. These help them to glean particular trends and patterns from the data and also offering simulations and predictions concerning 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 information at its disposal, and data mining becomes the core of advanced methodologies that deal with information overload.
Data Mining Technology
So let’s understand this technique of data mining. Data mining uses a technology known as machine learning and visualization and statistical methodologies in representing and discovering knowledge that is easily understood by humans. The main idea here is to extract, reduce complexity, or mine, useful and relevant information from databases.