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Data mining What is it, what is it for and how does this method work?

The data mining is a technique used to study the behavior of a population and how they act in the network. The main feature of this tool is that the analysis process is as automatic as possible.

In the following paragraphs you will find all the information related to this topic and you will know what data mining is for in computing. In addition, we will show you the mining process of data in a simple way.

If you want to become an expert and know which are the most used techniques today, you will have to continue reading this post.

What is data mining and what is this tool for?

It is an artificial intelligence method that is used to statistically know different patterns of a population using computer tools. When referring to population, the technical term of statistics must be understood, which is the set of users who have a certain characteristic that unites them.

In this way it is possible to analyze how a group of people react to fashion or before any other fact that is of business interest. Data mining is also used for espionage and to know the behaviors on the network that a large group of individuals or certain elements have.

Data mining process How is this massive collection of information carried out?

To do it data mining need to set sample. For this, it is necessary to know the different variables that will be studied and the possibility of calculating and inferring the parameters interested in obtaining information. Then it will be useful to dump into statistical graphical methods, especially histograms or circular distribution, the analyzes that have been performed on the sample.

In this way, it is possible to know which data were left out, which ones were presented as null and the dispersion or correlation of two variables. Once these points have been analyzed the data must be prepared to carry out the processing of them in the most automatic way possible. When the stage is ready, you can only decide what kind of technique to use in data mining.

To obtain a model knowledge about information found through the use of data mining, one can infer in the first concepts and relate them with other variables that will help to study the correlation or dispersion of sample data. Finally, you must interpret the data obtained using a model and validating them. This is done to draw conclusions about the massive behavior that the sample has in a certain variable.

Data mining techniques What are the most effective and used?

The techniques used by data mining are the following:

  • Linear regression. Statistical regression is a variable used to find relationships between data, making it a quick and efficient technique. But for many jobs the results it brings are not enough.
  • Other statistical models. In this data mining technique, different designs are used that serve to indicate the relationship between two or more factors and how a given variable behaves before.
  • Neuron networks. It is based on the interconnection of neurons that occurs in the central nervous system of animals. In this way it is possible to know how one network works and how it collaborates with another in the total set. Discrimination and problem solving techniques are used that cannot be separated from the general theme, among others.
  • Decision trees. A predictive model is used given a database in which logic diagrams are built and the behavior of a certain event is verified. For this case, the algorithms C4.5 and ID3 are used, among other examples.
  • Analysis by association. It is one of the most common and easy to implement because the different sample data is grouped and what happens in the data set is verified according to the algorithms used.
  • This technique is also called Vector Grouping and consists of associating vectors according to established criteria, from which characteristics that are common to the sample are obtained according to a given input.

Usefulness of data mining How can it be applied to various sectors?

Data mining can currently be used in the following industries:



It is one of the most important and general uses of the MD. This is because it can be used in the correlation and dispersion of 2 variables and know its behavior in a much easier way than a sample or the total population has. In addition, you can study the Variance for to know what kind of deviation a variable has with respect to the set of elements. Other variables you can find are the series and the discriminating of a sample.


In computing it is used for algorithm construction to optimize a series of data that occurs in a certain behavior. This way you get better results and you can add other random factors to know your reaction. Data mining is used in artificial intelligence to analyze the data automatically. You will also find data mining in the systems that were created by experts, with and without knowledge of the situations, and in parallel analysis processes.

Internet behavior

Data mining on the web is used by companies and is responsible for analyzing the behavior that users have on the Internet when they browse. They then use this information to serve advertisements. This is related to browser cookies, so this activity is not always ethical because the information is obtained without the consent of the person.


Analysis of the return on an investment project it is key and you can know a very precise number if you use data mining. This is because companies can know in advance to the disbursement of the money what attitudes the market in which they want to invest has.

Video game

Video game

Knowing the taste that consumers have is essential for the success of this sector. So companies use data mining to find out the gamers preferences and thus offer a better service that is adapted to all requirements.

Manufacture of merchandise

Industries are one of the sectors of the economy that uses data mining the most. This is due to the possibility that this technique offers to predict buyer behavior and competitor analysis. Based on these reports, it is possible to make a much more realistic production budget and, therefore, purchases are better planned and thus obtain higher profits.

Employee analysis

Companies use this mass research technique in their human resources departments. They do this because they can gain insight into why some employees are successful in their jobs and why others don’t.

Genetic mapping

Data mining can be used to find out the genetic mapping of certain people. This helps to relate them to other variables and knowing why they choose or behave in a certain way.

List of the main tools used for data mining

We will show you below the main tools that can be used to perform a successful data mining:

This data mining tool is used to carry out research related to organizations industries. It is based on the study of income and expenses, focusing on risk reduction to increase profitability. This program is developed for different operating systems, so the analysis processes can be carried out without limitations. In addition, it has modules that include graphics and tools that allow a better interpretation of the study.

Neural Designer

In this case it is a computer program that is used to graphically interpret neural network models. It does this through algorithms that are easy to use in healthcare companies, engineering and banks, among other sectors. You have a free trial to know all the functions and analyze all the benefits that can be obtained.

Machine learning Orange is a program used to create workflows and know a series of components that are related to two or more factors of interest. It is open source and is characterized by the ease with which it offers the results, since it does so with very intuitive graphics.

This German platform allows you to obtain information about data of interest. It does this by validating different statistical models and ROC type. The results are shown graphically so learning is much simpler.

It is an open source library that can be downloaded from its website and models can be created to analyze marketing, energy, health and industrial projects, among other sectors. It shows the results by means of regression output models in which you can assign patterns and make predictions about the future behavior of the variables.