DAX Filtering and Row Context in Power BI

In this blog post, I will explain what filtering and row context are, how they affect your calculations, and how to use them correctly. I will also show you some examples and tips to help you understand these concepts. 

Filtering Context in Power BI

Filtering context is the set of filters that are applied to your data before DAX starts to calculate your formulas. These filters can come from different sources, such as:

  • Slicers, visuals, or report filters that you use to interact with your data
  • Relationships between tables that you create in your data model
  • Filter functions that you use in your DAX formulas, such as FILTER, CALCULATE, or ALL

To use filtering and row context in Power BI, you need to understand how they interact with each other and with your DAX formulas. Filtering context always applies before row context. This means that filtering context filters the table first, and then row context selects one row from the filtered table.

NOTE: You can modify the filtering context using functions like CALCULATE or CALCULATETABLE. These functions allow you to change or remove the filters that are applied to your data, and create a new filtering context for your calculations.

Row Context in Power BI

  • Row context is like looking at one row of data at a time in Power BI. 
  • Created by calculated columns and iterator functions. 
Example 1: Row context in calculated columns

Calculated columns has row context by default.

SalesAmount = Sales[Units Sold] * Sales[Price/Unit] 

This formula multiplies the units sold column with price per unit from the sales tables for each row, using the row context to understand which row's values to use.

NOTE: A row of matrix is not a row context, but it defines the filter context.

Example 2: Row context in measures

Measures do not have row context by default. To add row context to a measure, you need to use an iterator function, such as SUMX, AVERAGEX, or FILTER, that loops over the rows of a table and performs a calculation for each row.

Kindly refer SUM vs SUMX in Power BI: What’s the Difference and When to Use Them? to understand why I used an iterator function.

Row context does not pass on to other tables. This means it only influences the table you are currently going through and doesn't impact any linked tables.

For example, if you have two tables, Sales and Products, that are related by a ProductID column, and you want to calculate the total sales per product category, you cannot use a formula like this:

TotalSalesCategory = SUMX(Sales, Sales[SalesAmount] * Product[Category])

Above formula will not work, because the row context created by SUMX only affects the Sales table, and not the Products table. To access the values of the Products table, you need to use a function like RELATED or RELATEDTABLE, which can follow the relationship between the tables and get the values from the related table.

Difference Between Filtering and Row Context

Features Filtering Context Row Context
Scope Impacts the entire table Operates on a single row at a time
Effect on Rows Filters out specific rows, rendering them invisible Selects one row, using its values for calculations
Presence Always present, created by default Created selectively during table iteration or when we insert new calculated column
Dynamic Nature Dynamically changes with data interactions Created explicitly, does not dynamically change

Conclusion:

Mastering filtering and row context in Power BI is important for accurate and insightful data analysis. Understanding their roles empowers users to create precise DAX formulas, ensuring calculations align with specific data subsets. 

I hope this blog post helped you understand how to use DAX Filtering and Row Context in Power BI. If you have any questions or feedback, please leave a comment below. I would love to hear from you. Thank you for reading!

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