Which term refers to the act of extracting useful insights from large sets of data?

The term that refers to the act of extracting useful insights from large sets of data is data mining. This process involves discovering patterns and knowledge from large amounts of data. Data mining employs various techniques from statistics, machine learning, and database systems to find patterns and correlations, ultimately leading to meaningful information and insights that can inform decision-making.

Data mining is often used in fields such as marketing, surveillance, fraud detection, and scientific discovery, where identifying trends and patterns in large datasets is crucial. The approach can handle various data types and is designed to analyze data sets that are too large for manual analysis. The outcome of data mining can include predicting future trends, behaviors, or events.

In contrast, data profiling focuses on analyzing and understanding the structure, content, and quality of the data itself rather than extracting insights. Data extraction refers to the process of retrieving data from various sources, often as a preliminary step before analysis. Data analysis encompasses a broader range of activities aimed at inspecting, cleansing, transforming, and modeling data to discover useful information, but does not specifically encapsulate the nuanced extraction of insights from patterns, which is the core characteristic of data mining.