What happens to unattended missing values while reading a dataset?

When a dataset is read, unattended missing values are set to missing. This reflects the approach taken by SAS when it encounters data that is not present in the dataset. Missing values indicate that the data is unknown or not applicable, and it is vital for data integrity to maintain this state rather than altering them to other values, such as zero or any default character.

By keeping the missing values as they are, SAS allows analysts and researchers to handle these instances appropriately in their analyses, ensuring that any calculations or statistical modeling accurately reflect the true nature of the data. In datasets, it's essential for missing values to be identified clearly so that downstream data processing and analysis can consider how to manage these gaps without introducing bias or misleading conclusions.