General decision-making generally includes eight basic steps: finding problems, determining goals, value criteria, drawing up plans, analyzing and evaluating plans, optimizing plans, testing and verifying, and general implementation. Data mining is a decision support process, which helps decision makers to adjust market strategies, reduce risks and make correct decisions by analyzing enterprise data with high automation and inductive reasoning.

Data analysis methods commonly used in data mining mainly include classification, regression analysis, clustering, association rules, characteristics, variation and deviation analysis, web page mining and so on. They mine data from different angles. So as to facilitate decision makers to make correct choices. Classification is to map the data items in the database through the classification model. Regression analysis method reflects the temporal characteristics of attribute values in the transaction database, while cluster analysis is mainly used in customer group classification, customer background analysis, customer purchase trend prediction, market segmentation and so on. Association rules are rules that describe the relationship between data items in a database. ...

If you want to know more about data mining, I suggest you go to official website and consult with CDA data analysts. CDA Data Analyst course not only cultivates students' hard data mining theory and Python data mining algorithm skills, but also cultivates students' soft data governance thinking, business strategy optimization thinking, mining management thinking, algorithm thinking and predictive analysis thinking, so as to improve students' data insight in an all-round way. Click to make an appointment for a free audition class.