Which type of filter is used on data elements that are measures?

The appropriate choice for filtering data elements that are measures is the range filter. This type of filter allows users to specify a minimum and maximum value to include in the analysis, making it particularly useful for quantitative data. Measures often represent numerical values such as sales figures, quantities, or other metrics where defining a specific range is beneficial to gain insights into the data.

Using a range filter enables analysts to focus on particular subsets of data that fall within certain numerical limits, facilitating a more precise and relevant analysis of the data. This is especially valuable in scenarios where you want to exclude outliers or focus on a specific segment of the distribution, enhancing the decision-making process.

Other types of filters, such as list filters, are more suited for categorical data, allowing the selection of specific elements from a predefined list. Expression filters are used to filter based on calculated values or custom logic, while relative time filters are designed to handle time-based data. Each of these options serves its distinct purpose but does not cater effectively to the specific needs of filtering numerical measure elements as the range filter does.