How can you validate data during the DATA step execution?

Validating data during the DATA step execution is effectively achieved by including conditional statements combined with the PUT statement. This approach allows programmers to assess and confirm the integrity and correctness of their data as it is being processed.

When conditional statements are used, one can implement logical checks to verify that data meets certain criteria. For instance, you can check for missing values, ensure that data falls within expected ranges, or validate that categorical variables contain expected values. The PUT statement then enables the output of messages or variable values to the log, allowing programmers to monitor these validations in real-time as the DATA step executes. This immediate feedback helps in identifying and addressing data issues promptly during processing.

In contrast, while using PROC PRINT to display data can be helpful for reviewing and debugging after the DATA step has completed, it does not provide real-time validation during execution. Similarly, sorting data might assist with organization but does not validate correctness. Creating backup copies of the dataset is a good practice for data management but does not facilitate the validation of specific data integrity during the processing phase. Thus, incorporating conditional checks and the PUT statement is the most effective means of validating data dynamically within the DATA step.