Why ALL function for removing filters in Power BI? - Purpose & Use Cases

The Big Idea

What if you could instantly ignore filters in your reports without changing anything manually?

The Scenario

Imagine you have a sales report filtered by region, and you want to see the total sales across all regions regardless of the current filter. Doing this manually means you have to copy data, remove filters one by one, or create multiple versions of the report.

The Problem

Manually removing filters is slow and error-prone. You might forget to remove a filter or accidentally change other settings. It's hard to keep reports consistent and up to date when you have to do this repeatedly.

The Solution

The ALL function in Power BI lets you ignore filters easily. It removes filters from a table or column so you can calculate totals or other values without changing your report filters. This keeps your reports accurate and dynamic.

Before vs After

✗ Before

Calculate Total Sales ignoring filters by copying data and removing filters manually.

✓ After

Total Sales All = CALCULATE(SUM(Sales[Amount]), ALL(Sales[Region]))

What It Enables

You can create dynamic measures that show totals or comparisons ignoring current filters, making your reports smarter and more flexible.

Real Life Example

A sales manager wants to see each region's sales as a percentage of total company sales, even when filtering by product category. Using ALL removes the product filter from total sales calculation.

Key Takeaways

Manual filter removal is slow and risky.

ALL function removes filters easily in calculations.

This enables accurate, flexible reporting with dynamic totals.