Understanding the Sort By Column Feature
The Sort By Column feature in Power BI is a fundamental data modeling capability that enables you to control how data appears in your visualizations by sorting one column based on the values of another column. While this might sound like a simple concept, it's incredibly powerful and essential for creating meaningful, accurate reports. This feature is particularly valuable when the default sorting behavior—whether alphabetical or numeric—doesn't align with the logical or business-specific order you need to present in your analysis.
Think of Sort By Column as a way to tell Power BI: "I know this column contains text that would normally sort alphabetically, but I want you to use these numbers from this other column to determine the correct order instead." This becomes the permanent sorting behavior for that column across your entire report, affecting every visualization, slicer, and filter that uses it.
Why Default Sorting Creates Problems
When you first bring data into Power BI, the platform applies default sorting behaviors based on data types. Numeric columns sort by their numerical values (1, 2, 3, 10, 20, 100), while text columns sort alphabetically (A, B, C, etc.). While this works perfectly well in many scenarios, it creates significant problems when the alphabetical or numeric order doesn't match the logical or contextual order your business needs.
Let's examine how this manifests in real-world scenarios:
Default Sorting Behavior | How It Works | When Problems Occur |
Numeric columns | Sort by number value (ascending or descending) | Generally works fine; rarely causes issues |
Text columns | Sort alphabetically (A-Z or Z-A) | Creates illogical ordering when text represents sequential concepts (months, sizes, priorities) |
Date columns | Sort chronologically when formatted as dates | Problems arise when dates are stored as text |
The Classic Month Name Problem
The most common example of this issue involves month names. Imagine you're creating a sales report that shows revenue by month, and you place "Month Name" on the axis of your chart. Power BI will sort these months alphabetically, resulting in an order like: April, August, December, February, January, July, June, March, May, November, October, September.
This alphabetical arrangement completely destroys the time-based narrative of your data. When a business user looks at this chart, they can't easily identify trends over time because the months aren't in chronological order. The line graph that should show a smooth progression through the year instead jumps erratically from April to August to December, making it nearly impossible to spot seasonal patterns or month-over-month growth. This is where Sort By Column becomes not just helpful, but essential.
How Sort By Column Works: The Solution
The Sort By Column feature works by establishing a relationship between two columns in your data model: the display column (what users see) and the sort column (what determines the order). The display column typically contains descriptive text that's meaningful to users—like "January", "February", "March"—while the sort column contains values that represent the correct sequential order—like 1, 2, 3.
When you configure Sort By Column, Power BI stores this configuration in the data model itself. This means the sorting behavior persists across all reports, pages, and visuals. You set it once in the data model, and every single visual that uses that column will automatically respect this sorting rule. There's no need to manually adjust sorting in each individual chart, table, or slicer.
Step-by-Step Implementation Process
Applying Sort By Column is a straightforward process, but it requires you to work in the Data View rather than the Report View. Here's how the process unfolds:
Step | Action Required | Specific Details | What Happens |
1 | Switch to Table View | Click the Data icon in the left navigation panel | You'll see your data tables in a spreadsheet-like view |
2 | Locate your display column | Find the column you want to sort (e.g., EnglishMonthName) | This is the column users see in reports |
3 | Select the column | Click on the column header | The entire column becomes highlighted |
4 | Access the Columns Tool tab | Look at the ribbon menu at the top | This tab contains data modeling tools |
5 | Click "Sort by Column" | Find this button in the Modeling ribbon | A dropdown menu appears with available columns |
6 | Choose your sort column | Select the column with sequential values (e.g., MonthNumberOfYear) | Power BI validates the relationship between columns |
7 | Verify the change | Return to Report View | All visuals using this column now sort correctly |
Once you've completed these steps, the sorting is permanently configured in your data model. Every existing visual updates immediately, and any new visuals you create will automatically use this sorting order.
Complete Walkthrough: Sorting Month Names
Let's walk through a complete, real-world example using the AdventureWorks database, which is a standard sample database used for learning Power BI. This example demonstrates the entire process from problem identification to solution implementation.
Initial Setup and Configuration
Before we can address the sorting issue, we need to establish our data environment. This involves connecting to the data source and creating the appropriate relationships between tables.
Component | Specific Details | Purpose |
Data Source | AdventureWorksDW sample database | Provides realistic business data |
Primary Tables | DimDate (dimension table) & FactInternetSales (fact table) | Date attributes and sales transactions |
Required Relationship | OrderDateKey (FactInternetSales) ↔ DateKey (DimDate) | Links sales transactions to dates |
Relationship Type | Active, one-to-many relationship | Ensures proper data filtering |
Cleanup Required | Remove any additional relationships to DimDate | Prevents ambiguous relationship paths |
After establishing your data connections, create a visualization—an Area Chart works well for this example. Configure the chart by placing SalesAmount in the Values field and EnglishMonthName in the Axis field. This creates a sales trend chart where each month's total sales are displayed.
Observing the Problem
When you first create this visualization, you'll immediately notice the problem. The months appear in alphabetical order across your axis, creating a confusing, non-chronological display:
What You See | What You Need | Why It Matters |
April, August, December, February, January, July... | January, February, March, April, May, June... | Users expect chronological progression |
Data points jump erratically across the chart | Smooth progression showing trends over time | Trend analysis becomes impossible |
Cannot identify seasonal patterns | Clear view of quarterly or seasonal changes | Business insights are obscured |
Month-over-month comparisons are meaningless | Adjacent months for meaningful comparison | Decision-making is impaired |
If you click the three-dot menu in the upper right corner of the visual and select "Sort by," you'll see that Power BI only offers you two sorting options: sort by SalesAmount (which orders months by revenue) or sort by EnglishMonthName (which toggles between A-Z and Z-A alphabetically). Neither option gives you chronological month order because Power BI doesn't inherently know that "January" should come before "February"—it just sees them as text strings to be sorted alphabetically.
Implementing the Solution
The solution lies in using the MonthNumberOfYear column that exists in the DimDate table. This column contains numerical values (1, 2, 3, 4...12) that correspond to each month's position in the calendar year. By telling Power BI to sort EnglishMonthName based on these numerical values, we establish the correct chronological order.
Navigate to the Data View, select the EnglishMonthName column, go to the Modeling tab, click "Sort by Column," and select MonthNumberOfYear. The moment you apply this setting, Power BI creates a binding between these two columns in the data model.
The Transformation
When you return to Report View, the transformation is immediately visible and dramatic:
Aspect | Before Sort By Column | After Sort By Column | Impact |
Month Sequence | April, August, December, February, January... (Alphabetical) | January, February, March, April, May, June... (Chronological) | Logical time progression restored |
Trend Lines | Erratic, jumping between non-sequential months | Smooth progression showing actual trends | True business patterns emerge |
User Understanding | Confusing, requires mental reordering | Intuitive, matches natural expectations | Faster insights, better decisions |
Data Analysis | Month-over-month comparisons impossible | Easy comparison of consecutive periods | Meaningful performance analysis |
Visual Aesthetics | Appears broken or incorrect | Professional, polished appearance | Enhanced credibility |
The chart now tells a coherent story. If sales increase from January through March, then dip in April, you can see this pattern clearly. Seasonal trends become obvious. The visualization has transformed from a confusing jumble into a powerful analytical tool.
