ALL() Function in Power BI

Syntax of ALL() Function in DAX

The ALL function in Power BI is a filtering function that removes or modifies filters on specified columns or tables within a dataset. It allows for temporarily altering the filtering context, enabling comprehensive analysis and calculations across the entire dataset, disregarding existing filters. This function is valuable for gaining insights and making informed decisions by providing an unobstructed data view without constraints. The syntax of the ALL function in PowerBI DAX is quite straightforward. It looks like this -

Parameters of ALL() Function in DAX

Here are the parameters of the ALL function in Power BI in a tabular format -

Return Value of ALL() Function in DAX

When you use the ALL function in Power BI, it returns the table or column with all filters removed. This means you get a clear and unfiltered view of your data, allowing you to perform calculations and analysis without any filter constraints.

Exceptions of ALL() Function in DAX

While the ALL function in Power BI is a versatile tool, there are a few points you should keep in mind while using it -

• Context Matters - The effect of the ALL function in Power BI depends on the context in which it's used. It might only sometimes remove all filters if there are other functions or expressions involved. The interaction with other functions and filters can affect the outcome.
• Multiple Tables - When dealing with relationships between multiple tables, using the ALL function in Power BI might require additional considerations to achieve the desired results. The relationships between tables can influence the way filters are removed.
• Performance Impact - Using the ALL function in Power BI extensively in complex calculations or queries can potentially impact query performance. Using it judiciously is important, especially in scenarios involving large datasets.
• Column Interactions - Applying the ALL function to a specific column might lead to unexpected results when interacting with other columns in calculations. The removal of filters from one column can affect calculations involving related columns.

How Does The All() Function In Dax Work?

The ALL function in DAX is a data analysis expression used to alter the filtering context of a table or column, temporarily removing filters and enabling comprehensive calculations and analysis across the entire dataset. The ALL function in Power BI works as a filter modifier, allowing you to manipulate the filtering context of your data. When you use ALL, it clears or modifies filters on the specified table or column, providing a clean slate for calculations and analysis.

Imagine you're looking at a dataset with various filters applied, like filtered by region or category. Applying ALL to a table or column wipes away these filters, enabling you to view the data without any restrictions. This is particularly useful when you want to perform calculations across the entire dataset, ignoring the applied filters temporarily.

Consider a scenario where you're examining sales data for various products. By applying filters for specific products, you might focus on insights for a specific product. However, if you want to assess the ratio of product sales to the total sales across all regions, the ALL function comes into the picture. Using the ALL function on the product table, you can neutralize any filters, ensuring that the ratio calculation considers the complete sales dataset. This enables you to derive a more comprehensive understanding of each product's performance relative to the entire sales landscape, making strategic decisions based on a broader perspective.

Examples

Suppose you have a sales dataset containing information about different regions and their respective sales amounts. The dataset includes two columns - "Region" and "Sales Amount". Now, you want to calculate the contribution of each region's sales to the total sales. You can use the ALL() function to temporarily disregard any filters applied to the "Region" column and compute the ratios accurately.

For this, we will create a new measure, "Ratio To Total Sales", representing the ratio of regional sales to total sales using DAX query as shown below -

the "Ratio To Total Sales" measure calculates the ratio of the sum of sales for each region to the sum of total sales across all regions. The ALL function removes any filters applied on the "Region" column, ensuring that the calculation considers the entire dataset's sales amount.