Imagine you have a sales dashboard with multiple filters. You add a context filter on Region. What happens to other filters applied after the context filter?
Think about how Tableau processes filters step-by-step.
Context filters create a temporary table that other filters use as their data source. This means other filters only see data after the context filter is applied.
Given a context filter on 'Category' set to 'Furniture', what will the LOD expression { FIXED [Sub-Category] : SUM([Sales]) } return?
Remember that context filters affect the data before LOD calculations.
The context filter limits data to Furniture category first. Then the FIXED LOD calculates sales per Sub-Category within that filtered data.
You have a dashboard with a context filter on 'Year' set to 2023 and a regular filter on 'Region'. Which visualization behavior is correct?
Think about how context filters set the data scope first.
The context filter on Year limits data to 2023 first. Then the Region filter applies on that subset, so the visualization shows data for 2023 and selected Region.
You notice your Tableau dashboard runs faster after adding a context filter on 'Country'. Why is this happening?
Think about how Tableau processes data internally with context filters.
Context filters create a temporary table with filtered data. Other filters work on this smaller table, reducing processing time and improving performance.
You have a dataset with millions of rows. You want to filter sales data to only 'Electronics' category and then apply multiple other filters on sub-categories and regions. What is the best approach to optimize filtering and ensure correct results?
Consider how context filters reduce data before other filters apply.
Setting the broadest filter (Category = Electronics) as a context filter reduces data size early. Other filters then work on this smaller dataset, improving performance and accuracy.