What are the differences between data mining and data analysis?

1. Definition of data mining

Data mining refers to the automated process of classifying large data sets to identify trends and patterns and establish relationships through data analysis to solve business problems. In other words, data mining is the process of extracting from large amounts of incomplete, noisy, fuzzy, and random data information and knowledge that is implicit in it and that people do not know in advance but is potentially useful. .

2. Difference from data analysis

Data analysis and data mining both discover knowledge from the database, so we call data analysis and data mining knowledge discovery in the database. But strictly speaking, data mining is the true knowledge discovery in database (KDD).

Data analysis is to obtain knowledge of database-based data representation from the database through statistics, calculation, sampling and other related methods. In other words, data analysis is to obtain some representational information from the database. Data mining is a technology that obtains deep knowledge (such as regularities between attributes, or predictions) from databases through machine learning or mathematical algorithms and other related methods.