Which field type should a Data Analyst use to apply a top N filter?

To apply a top N filter effectively, a Data Analyst should utilize a discrete dimension. This type of field groups data points into distinct categories or segments, which is essential for identifying the top N items within those groups.

When a discrete dimension is used, Tableau can evaluate each category separately, allowing for a clear comparison and ranking based on a measure (like sales, for instance). The top N filter can then be applied to display only the highest performing categories according to the chosen measure, providing focused insights.

In contrast, a continuous measure would typically result in a range of values rather than distinct categories, making it less suitable for a top N filter. A calculated field involves more complex derivations that can complicate the filtering process. An aggregate measure provides summarized data across the entire dataset, which may not lend itself to identifying the top N items within specific groups or categories effectively. Hence, utilizing a discrete dimension is the most appropriate approach for this scenario.