Which process is used by large retailers to study trends?

Large retailers collect enormous amounts of transaction data every day, from till receipts to loyalty-card purchases. To turn that raw data into something useful, they use a process that searches through the data for hidden patterns, correlations, and trends, such as which products sell together or which items become popular in a particular season.

This process is data mining. It applies statistical and computational techniques to large data sets to discover regularities that are not obvious just by looking at individual transactions. A retailer that studies trends this way can decide what stock to reorder, how to plan promotions, and where to place products on shelves.

Selecting a subset of data or converting data from one format to another are steps that may support analysis, but they do not by themselves reveal trends; they are preparatory tasks. A point-of-sale system only records the transaction at the till and does not analyse patterns across many transactions.

Exam takeaway: when a question links large volumes of stored data to the discovery of trends or patterns, the expected term is data mining, not the tools that merely collect or reformat the data.