What is true about the use of filters within sets in LookML?

Using filters within sets in LookML allows for more precise data management and query optimization. When applying filters to sets, it is possible to exclude certain data points or dimensions easily. This means that users can create more focused segments of the dataset according to specific criteria, enhancing the relevance and accuracy of reports and visualizations produced in Looker.

The ability to easily exclude elements from sets means that you can dynamically adjust the data being analyzed without extensive rework or adjustments to the underlying model. This feature is particularly useful for analyzing trends, outliers, or segments of the data that are meaningful for specific analyses.

Regarding the other options: filters are not applied globally to all sets, as filters are typically localized to the specific set they are defined within. It's not necessary for filters in sets to be created beforehand, as they can be applied dynamically. Additionally, filters in sets do affect data retrieval in queries, contrary to the implication in the last option. They play a critical role in determining what data is included in the results returned to users.