What is the process of discovering patterns and knowledge from large amounts of data known as?

The process of discovering patterns and knowledge from large amounts of data is known as data mining. This term encompasses various techniques aimed at extracting meaningful information from vast datasets, which may include identifying trends, correlations, outliers, or any significant patterns within the data. Data mining uses methods from machine learning, statistics, and database systems to automate the discovery of insights that would be too tedious or complex for manual analysis.

In contrast, data analysis typically refers to the broader scope of examining and interpreting data to derive conclusions, which can include data mining as one of its components but is not limited to pattern discovery alone. Data collection focuses on gathering raw data from various sources, serving as the foundational step that precedes data mining. Lastly, data visualization is the practice of representing data graphically, making it easier to understand and interpret, but it does not inherently involve the extraction of patterns or knowledge from the data itself. Thus, data mining is specifically aligned with the discovery of actionable insights within large datasets, making it the correct answer.