What is Stack Marks in 'Analysis' in Tableau?

 In Tableau, "Aggregated Measures" in the context of "Stack Marks" refers to how data points are combined or stacked when you have multiple measures (quantitative values) in your visualization. Tableau allows you to create various types of charts and visualizations, and when you have multiple measures, you can choose how these measures are aggregated and displayed within the visualization.

"Stack Marks" is a feature commonly used in visualizations like bar charts, area charts, and stacked bar charts, where you want to represent the relationship between different measures for each category or dimension in your data. When you stack marks, you are essentially combining the values of different measures for each category, and you can control how they are aggregated.

For example, if you have a dataset with sales and profit as measures and product categories as a dimension, and you create a stacked bar chart, you can choose to stack the sales and profit measures together for each category. You can aggregate them using functions like SUM, AVG, MIN, MAX, etc., depending on your preference and the insights you want to convey.

Here's how you can work with Aggregated Measures in Stack Marks:

1. Drag the dimension (e.g., Product Category) to the Columns or Rows shelf.
2. Drag the measures (e.g., Sales and Profit) to the same shelf (Columns or Rows).
3. By default, Tableau will stack the marks using the SUM aggregation for each measure. This means that for each category, the total Sales and Profit values will be stacked on top of each other.
4. You can customize the aggregation method and other settings by:
5. Right-clicking on a measure pill in the shelf and selecting "Measure" to choose a different aggregation function (e.g., AVG, MIN, MAX).
6. Editing the "Stack" settings in the Marks card to change the stacking order or customize the offset.

By adjusting these settings, you can control how the aggregated measures are displayed in your Tableau visualization, making it easier to analyze and interpret the data based on your specific requirements.