Whenever you add a measure to your view, an aggregation is applied to that measure by default. This default is controlled by the Aggregate Measures setting in the Analysis menu.
If you decide you want to see all of the marks in the view at the most detailed level of granularity, you can disaggregate the view. Disaggregating your data means that Tableau will display a separate mark for every data value in every row of your data source.
To disaggregate all measures in the view:
- Clear the Analysis >Aggregate Measures option. If it is already selected, click Aggregate Measures once to deselect it.
When Aggregate Measures is selected, Tableau will attempt to aggregate measures in the view by default. This means that it collects individual row values from your data source into a single value (which becomes a single mark) adjusted to the level of detail in your view.
The different aggregations available for a measure determine how the individual values are collected: they can be added (SUM), averaged (AVG), or set to the maximum (MAX) or minimum (MIN) value from the individual row values.
For a complete list of the available aggregations, List of Predefined Aggregations in Tableau.
The level of detail is determined by the dimensions in your view—for information about the concept of level of detail, see How dimensions affect the level of detail in the view.
Disaggregating your data can be useful for analyzing measures that you may want to use both independently and dependently in the view. For example, you may be analyzing the results from a product satisfaction survey with the Age of participants along one axis. You can aggregate the Age field to determine the average age of participants or disaggregate the data to determine at what age participants were most satisfied with the product.
Disaggregating data can be useful when you are viewing data as a scatter plot. See Example: Scatter Plots, Aggregation, and Granularity.
Note: If your data source is very large, disaggregating the data can result in a significant performance degradation.