In analytics, you often need to perform several data manipulation steps in sequence—such as selecting columns, filtering rows, creating new variables, and arranging results. Rather than writing separate commands, you can use the pipe operator '%>%' to chain these operations together, making your code cleaner and easier to follow. This approach is especially useful when cleaning and preparing data for analysis, as it allows you to express a series of transformations as a single, readable pipeline. Now, you will practice chaining multiple dplyr verbs using pipes to achieve a real-world data cleaning task.