Get to Know The Concept of Data Mining

Information management at this time is very important. Where, each data will be very influential in terms of making a decision that will be taken by the user. A term that is well known today by practitioners in the IT world is data mining.

So what is data mining? Then what are the functions and features it has? In this article, we will discuss some of these things to help improve your understanding of the concept of data mining software.

Definition of Data Mining

Understanding data mining is the process of collecting important information on a large data set. The data collection can be done through the process of calculating statistics, mathematics, and the use of AI ( Artificial Intelligence ) technology.

Another term for data mining itself can mean data mining in the form of a tool to perform analysis with more accurate information filtering techniques. This technique is usually done to find certain patterns that still have relevance to the goals or instructions of the user ( user ).

Functions of the Application of Data Mining

Next, you must also understand some of the functions or uses of data mining itself.

1. Association

First, association is the process of identifying relationships (relationships) from each event or event that has occurred at a certain time.

2. Classification

Second, classification serves to conclude several definitions of characteristics in a group or groups. An example is customers who switch services because they cannot compete with other customers.

3. Clusterization

Third, clusterization is the process of identifying groups of products or goods that have special characteristics.

4. Descriptive

Fourth, descriptive is a function for the purpose of understanding more deeply about the data, so that you can observe any changes in behavior in the information.

5. Forecasting

Fifth, forecasting is a data forecasting technique that is carried out to obtain an overview of the value of a data in the future according to the collection of information with a large amount of information. An example of the application of forecasting is data related to forecasting the number of lecturers entering state universities.

6. Predictive

Sixth, predictive is a function that is used to explain a process in determining a certain pattern in a data. This pattern is used by various variables in the data.

7. Sequencing

Finally, sequencing is the process of identifying each different relationship at a certain time period. An example of sequencing itself is a customer who visits a store continuously (repeatedly).

Conclusion

Data mining is one way to collect information or data with a large size. There are 7 uses of data mining, namely association, classification, clusterization, descriptive, forecasting, predictive, and sequencing . Make sure you implement data mining according to business needs and adapt to your company’s stakeholders.