Data mining is the process of extracting meaningful patterns and knowledge from large sets of data. It involves applying algorithms to search for patterns within data collections, which can include databases and other data repositories. The goal is to uncover non-obvious insights that can be used for decision-making and predictive analysis.

The data mining process typically includes several key steps: data collection, data cleaning and validation to address errors and inconsistencies, model development and testing, and final deployment. During model development, various machine learning algorithms, such as regression, decision trees, and support vector machines, are employed to analyze the data effectively ²⁵.

Data mining is increasingly important in various fields, including marketing, education, and environmental science, as it helps organizations understand trends, customer behavior, and even predict natural disasters ⁴.

If you have more questions about data mining or its applications, feel free to ask!