How to Ignore Filters in Power BI

By default, every visual in Power BI interacts with others - click on a country in a slicer, and every chart on the page instantly filters down to show data for just that country. While this interactivity is powerful, there are times when you need a specific chart or number to stand its ground and ignore the filters. This guide will walk you through the two primary ways to make a visual ignore filters in Power BI: using an easy-to-use menu option, or by writing a bit of DAX code for more complex situations.

What Does It Mean to Ignore a Filter?

Imagine you have a sales dashboard. You might have a slicer to view performance by sales region. You also want a main KPI card at the top of your report that always shows the total company-wide sales, regardless of which region is selected. You want this main number to serve as a constant benchmark while you explore regional data.

If you don’t tell Power BI to ignore the filter for that KPI card, the number will change every time you select a new region, defeating its purpose. By instructing that specific visual to ignore the filter, you gain more control and can build more insightful reports. This technique is essential for creating dashboards that provide both high-level context and detailed, interactive analysis.

You can achieve this in two ways: through the user-friendly "Edit Interactions" feature or with more powerful DAX formulas like ALL() and ALLEXCEPT().

Method 1: Using Edit Interactions (The No-Code Approach)

The simplest way to control how visuals affect each other is by using Power BI Desktop's built-in "Edit Interactions" feature. This is a point-and-click method that doesn’t require writing any code and is perfect for most common scenarios.

Step-by-Step Guide to Edit Interactions

Let’s walk through the process using our sales dashboard example. We have a slicer for "Region" and a card visual displaying "Total Sales."

1. Select the Slicer or Filtering Visual: First, click on the visual that is doing the filtering. In our case, this is the "Region" slicer. When you select it, you'll see a border appear around it.
2. Find the "Format" Tab and "Edit Interactions": With the slicer selected, go to the Format tab in the main ribbon at the top of the screen. In the "Interactions" group, you'll see a button labeled Edit interactions. Click it.
3. Choose the Interaction Behavior: Once you click "Edit interactions," you'll notice small icons appearing at the top corner of all the other visuals on your report page. These icons control how this slicer will affect them. You'll typically see a chart icon for "Filter" and a circle-with-a-line-through-it icon for "None".
4. Set the Interaction to "None": To make our "Total Sales" KPI card ignore the slicer, simply hover over the card and click the None icon (the circle with the slash through it). The icon will become highlighted, confirming your choice.
5. Turn Off Edit Interactions: Click the "Edit interactions" button a second time to exit the editing mode.

That's it! Now, when you select a region in your slicer, all other visuals will update, but your "Total Sales" card will remain unchanged, always showing the grand total. You can repeat this process for any combination of visuals and slicers to customize your dashboard's behavior.

When to Use Edit Interactions

• When you need a visual on a specific page to ignore a slicer on that same page.
• For straightforward scenarios where you want a complete "on" or "off" filtering interaction.
• When you prefer a quick, visual method without writing formulas.

Method 2: Using DAX Functions (The Flexible & Powerful Approach)

Sometimes, "Edit Interactions" isn't enough. What if you need a calculation that ignores filters within a formula itself, or if the filtering logic is more complex? This is where DAX (Data Analysis Expressions) comes in. By creating a DAX measure, you can precisely define which filters to ignore and which to respect.

The primary DAX function for this job is ALL(), along with its helpful cousins ALLEXCEPT() and REMOVEFILTERS().

The ALL() Function

The ALL() function returns all the rows in a table or all the values in a column, ignoring any filters that might have been applied. It's the most common tool for creating measures that calculate a total percentage or a ratio against a grand total.

Let's create a new measure for our "Total Sales" card that will always show the grand total, regardless of any slicer.

Total Sales (Unaffected by Filters) = 
CALCULATE(
    SUM(Sales[SaleAmount]),
    ALL(Sales)
)

Here’s how this measure works:

• SUM(Sales[SaleAmount]): This is our base calculation, simply summing up the sales amount.
• CALCULATE(...): This is a DAX powerhouse. It modifies the context in which a calculation is performed. In other words, you give it an expression (like SUM) and then a set of filters to apply or, in our case, ignore.
• ALL(Sales): This is the magic ingredient. We are telling CALCULATE to perform the sum over the entire "Sales" table, effectively removing any active filters from the slicers or other visuals.

Once you create this new measure, you can place it in a KPI card. This card will now show the total company sales no matter what filters are applied anywhere in the report, without ever needing to touch the "Edit Interactions" button.

The ALLEXCEPT() Function

What if you want to ignore most filters but keep just one or two? This is where ALLEXCEPT() is incredibly useful.

Imagine you want to calculate the total sales for a given region, ignoring filters on product or date, but still respecting the region filter. The measure would look like this:

Total Region Sales (Ignore Other Filters) = 
  CALCULATE(
      SUM(Sales[SaleAmount]),
      ALLEXCEPT(Sales, Sales[Region])
  )

In this formula, ALLEXCEPT(Sales, Sales[Region]) tells Power BI to remove all filters from the "Sales" table except for the filter on the "Region" column. So, if a user selects "North" as the region and "Hats" as the product, this measure will show the total sales for the "North" region for all products, ignoring the "Hats" filter.

The REMOVEFILTERS() Function

In newer versions of DAX, REMOVEFILTERS() can be used as a more readable alternative to ALL(). It functions exactly the same way inside CALCULATE().

Our original ALL() measure can be rewritten like this:

Total Sales (Unaffected by Filters) = 
CALCULATE(
    SUM(Sales[SaleAmount]),
    REMOVEFILTERS(Sales)
)

Many developers prefer REMOVEFILTERS() because its name makes the formula's intention very clear: you are removing filters, not just selecting "all" rows.

When to Use DAX Over Edit Interactions

• For Reusability: A DAX measure can be used on any page in your report. "Edit Interactions" has to be configured page by page.
• Complex Logic: When you need to ignore some filters but not others (e.g., using ALLEXCEPT).
• Calculations like % of Total: When you need the "unfiltered" value inside another calculation, DAX is the only way. For example, to calculate a product's percentage of total sales:

% of Total Sales = DIVIDE(SUM(Sales[SaleAmount]), [Total Sales (Unaffected by Filters)])

Final Thoughts

Controlling filter interactions in Power BI is a fundamental skill that elevates your reports from reactive displays to insightful, storytelling dashboards. You learned two key methods: the simple 'Edit Interactions' menu for quick page-level tweaks and the powerful suite of DAX functions like ALL, ALLEXCEPT, and REMOVEFILTERS for creating robust, reusable calculations anywhere in your reports.

While mastering these Power BI features gives you granular control, all that manual setup and DAX wizardry takes a ton of time to learn and build out for every project. At Graphed, we felt this pain after spending years wrangling complex reports, so we created a platform where you can build them just by asking questions in plain English - no tricky menus or DAX formulas needed. Instead of clicking through menus to configure interactions, you can simply say, "Show me my sales KPI unfiltered by region" and our AI builds the live-updating visual for you in seconds, freeing you up to focus on the insights, not the setup.