What are the application fields of data mining?

Data mining is widely used. As long as the industry has a database of analysis value and demand, data mining tools can be used for purposeful mining and analysis. Common application cases mainly appear in the fields of retail, manufacturing, finance, financial insurance, communication and medical services:

(1) Shopping malls find certain association rules from the goods purchased by customers, and provide discounts, shopping vouchers and other promotional means to increase sales;

(2) Insurance companies establish prediction models through data mining to identify possible fraudulent behaviors, avoid moral hazard, reduce costs and improve profits;

(3) In the manufacturing industry, the production and testing of semiconductors will produce a large number of data, which need to be analyzed to find out the existing problems and improve the quality;

(4) E-commerce is playing an increasingly important role. Data mining can be used to analyze websites, identify users' behavior patterns, retain customers, provide personalized services and optimize website design.

The successful cases of some companies using data mining show the great vitality of data mining:

AutoTrader is the largest car sales website in the world. Every day, a large number of users click on the information on the website to seek information. It uses SAS software for data mining, analyzes the data every day, finds out the access mode of users, judges the preferences of products, and sets up specific services, which has achieved success.

Reuteres is a world-famous financial information service company, and the data it uses are mostly external data, so the data quality is the key to the company's survival, and the wrong components must be detected from the data. Reuteres uses SPSS/ Clementine, a data mining tool of SPSS, to build a data mining model, which greatly improves the error detection and ensures the correctness and authority of information.

Bath Export Company is one of the largest beer importers and exporters in the world. It trades in more than 80 overseas markets and sends 23,000 orders every week, which requires understanding the habits of each customer, such as brand preference. Bass Export solved the above problems well with IBM's intelligent miners.