Data Mining Applications

Data Mining Applications: As we already know, Data Mining is very useful and beneficial as we can dig deeper into the data so as to explore more about it and understand all of this in more detail. Data Mining is popularly and widely used in many different areas. In this section, we will discuss in detail as to where we can use the Data Mining.

Listed below are the areas where Data Mining is very popular/famous.

Let us know and understand each one of them separately in detail in order to know why and how we can use Data Mining in different fields as given above:

Education

Education and Data Mining can be called as two terms which we are most definitely going to hear a lot in the future and even today we hear those two terms together many times. The main motive and the goal of Educational Data Mining (EDM) is to retrieve or discover the knowledge of the data originating from the Environment which is Educational. There are several other motives/goals behind Education Data Mining such as studying and taking into account the effects of educational support, advancing on the scientific knowledge about learning and so on. Moreover, Educational Data Mining can be used for the purpose of taking accurate decisions and predicting the results of a student faster.

Fraud Detection

We lose a lot of money every year like billions of dollars because of the actions of frauds we see. The methods that we have been using for years in order to reduce fraud are nothing but time consuming and very difficult to understand. With the introduction to Data mining, we are well aided in providing significant/relevant patterns and changing/modifying the data into information that is valid and useful at the same time.  According to the experts, the ideal and faultless fraud detection system has to always protect information (whether confidential or not) of all the users.

Financial Banking

As we have discussed in the previous point that Fraud is very likely to happen in case if we continue using the traditional and conventional methods of Fraud Detection. Similar is the case with Financial Banking. As we all are aware of the fact that computerized banking is almost everywhere these days. There is a huge data generated on the daily basis. In these cases, Data mining can be proven extremely beneficial and applicable to solve or figure out the problems that are faced in banking and financial departments. We can do that by searching for patterns, correlations and other important information in the data of business and the prices in the market that are not straight away evident/obvious to the experts of these departments. The size of the data generated is very large or that were generated very quickly.

Corporate Surveillance

Corporate surveillance, in simpler words can be defined as the process of observing an individual or a group’s behavior as depicted by a corporation. The data that is being collected is frequently the data that are being used for the sole purpose of marketing or selling that to other corporations, but the data also has to be commonly shared with the government agencies. It can also be used for the businesses so as to adapt the need of the products that are required or suitable to their customers. The data can also be used for the purpose of direct marketing, for instance the advertisements on Google, Facebook, Yahoo, Instagram and others where the advertisements are generally intended for the users of these search engines. This process takes place by analyzing a user’s search history, emails, and other information like that.

Research Analysis

It has been proven many times that the methods of research are constantly being changed. As a matter of fact, it is very much evident since a very long time, that we have observed revolutionary changes/modifications in the field of research. Data mining is beneficial as it cleans the data, and pre-processes the data. The researchers are able to find the similar data from the database that will bring the changes in the field of research.

Retail Industry

Data Mining is very beneficial and an apparent great application in the Industry of Retail. There are a number of reasons why it is beneficial such as it gathers a substantial amount of data on the basis of on sales, purchasing history of a customer, the goods that were transported, daily consumption and daily services. In the Industry of Retail, the quantity of data that are gathered continually expands because of the increasing ease, availability and popularity.

Data mining in Retail industry is extremely helpful when we need to identify the buying patterns of a customer, and the trends that will be extremely beneficial for improving the quality of the customer services and hence, it will lead to the customer satisfaction.