Data mining is a process in which a large amount of data is analyzed to find some patterns and useful information. They are typically performed in databases that store the data in a structured format.
By “mining” a large amount of data, some confidential information is also obtained, which can be used in any other work.
Examples of Data Mining
A credit card company uses data mining to understand the buying habits of its members. While the company can study their shopping habits by analyzing the cardholders’ purchases, it can also know how the people of different places make more purchases.
At the same time, this information can be very important in offering specific promotions to that individuals. At the same time, with the same data, the pattern of their shopping can also be understood, irrespective of the country or any province.
This information is valuable for companies that want to advertise or start a new business.
Online services, such as Google and Facebook, mine a lot of data so that they can be able to offer targeted content and advertisements to the users.
While Google also analyzes similar search queries, it searches for such popular searches in specific areas and puts them in its autocomplete list (these are the suggestions that appear as soon as you type something).
By mining the user activity data, Facebook also receives information on many different topics; simultaneously, it targets the ads accordingly, which is based on the same information.
While data mining is mainly used for marketing purposes, there are many other uses. For example, healthcare companies can use this data mining to find links related to certain genes and diseases.
The meteorological department can also mine these data and find out the weather pattern and, with its help, can make a pre-conjecture about the other meteorologic events.
At the same time, traffic management can also mine these automotive data and make a pre-estimation of what kind of traffic levels will happen in the future, and according to that, you can make the right plans for highways and streets.
Data Mining Requirements
Data mining has two main requirements – a lot of data and computing power.
The more organized the data, the easier it will be to mine it properly and get useful information simultaneously.
So it is very important for any organization that wants to engage in data mining; they have to be proactive to select which type of data to log and how to store it.
When it comes to mining data, supercomputers and computing clusters are needed to process a petabyte quantity of data.