Which term describes the practice of analyzing data to derive actionable insights?

The term that describes the practice of analyzing data to derive actionable insights is data analysis. This process involves systematically applying statistical and logical techniques to describe and illustrate, condense and recap, and evaluate data. By interpreting data sets, patterns and trends can emerge, allowing organizations to make informed decisions based on the analysis.

Data analysis usually involves various techniques and tools that help in understanding complex data. The end goal is to turn raw data into meaningful information that can guide business strategies, optimize operations, or enhance customer experiences. It's a key aspect of data-driven decision-making and is fundamental across numerous fields, including business, research, and technology.

Other terms like data curation, data engineering, and data interpretation play different roles in the data lifecycle. Data curation focuses on organizing and maintaining data, data engineering involves the design and construction of systems for collecting and processing data, and data interpretation involves the subjective exercise of making sense of analyzed data. While each of these functions is important, they do not specifically refer to the act of analyzing data for actionable insights in the same way that data analysis does.