The term data mining is often used when it comes to the storage and management of information in the big data area. Many companies use data mining as a tool by enabling the systematic application of computer-based procedures to find patterns, trends and relationships within large databases.

It builds on various findings from the fields of computer science, statistics and mathematics by performing analyzes of databases. These analyzes pursue the goal of finding connections, patterns, trends and relationships between information within large databases and making them usable.

Data mining works in a purely automated manner, which results in both cost and time savings. Companies can then use the results provided to make decisions about strategies or problem solving more easily.


Data mining is mostly used for the achievement of several goals by companies. In order to achieve these goals, it has to do a variety of tasks.

This includes:

classification : Object data are divided into classes.

Segmentation: Combination of feature-like objects into groups.

Forecast: Prediction of unknown or new features.

Dependency analysis: Knowledge of connections and relationships between features of objects.

Deviation Analysis: Identification of objects whose characteristics are not dependent on other objects.

Significance for big data areas

While big data often serves as a framework for data mining, the latter does not tend to be linked to it. Because data mining only describes an analysis of data stocks for characteristics and relationships of individual objects. It is often used in the context of large databases, such as in the area of big data, but it can also be used for smaller databases.

Nonetheless, it can be found far more frequently in the fume cupboard on big data and uses the technical basis to effectively obtain information from existing data. In addition to artificial intelligence, it also uses statistical algorithms. This enables more structure and transparency to be promoted and more relevant results to be delivered, especially with large databases that are often confusing.

Who can benefit from data mining?

Data mining is already used in practice in a large number of areas, as it offers great potential for users. For example, it is currently widely used in finance, marketing and medicine, and even as a tool for police analysis. But data mining is also used for improved customer service and risk analyzes, for example by banks and insurance companies. It can also be used to analyze the buying behavior of customers and is therefore also very popular in the area of online shops.

The following articles also provide more on the subject of data and big data:


Image source:


I blog about the influence of digitalization on our working world. For this purpose, I provide content from science in a practical way and show helpful tips from my everyday professional life. I am an executive in an SME and I wrote my doctoral thesis at the University of Erlangen-Nuremberg at the Chair of IT Management.

By continuing to use the site, you agree to the use of cookies. more

The cookie settings on this website are set to "Allow Cookies" to provide the best browsing experience. If you use this website without changing the cookie settings or click "Accept", you agree to this.