How to Use Small Multiples in Power BI

Tired of trying to cram a dozen different data series onto a single chart? Small multiples in Power BI are the clean, simple, and powerful solution you're looking for. Instead of creating a complicated and cluttered visual, this feature splits your chart into a grid, giving each category its own mini-chart while keeping the scales consistent. This article will walk you through exactly what small multiples are, when to use them, and how to create and format them step-by-step.

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What Are Small Multiples?

Think of small multiples as a series of miniature, uniform charts displayed in a grid. Originally popularized by data visualization pioneer Edward Tufte, the idea is to use the same basic chart type (like a line or bar chart) and the same scales for each mini-chart, with the only difference being the data subset it displays. This makes comparing trends and patterns across different categories remarkably easy.

For example, instead of a single line chart with ten overlapping lines representing sales in ten countries, you could have a grid of ten separate line charts - one for each country. Immediately, you can see which countries are growing, which are flat, and which are declining without trying to follow a tangled mess of lines across a single visual.

You might also hear them called "trellis charts," "lattice charts," or "facet grids." Whatever you call them, their purpose is the same: to slice a complex dataset into understandable, bite-sized visuals for straightforward comparison.

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When Should You Use Small Multiples?

Small multiples are incredibly versatile, but they shine in a few specific scenarios. They are perfect when you need to break down a main measure by a dimension that has several categories.

Here are a few common use cases:

• Comparing time-series data: Analyze website traffic trends over the last quarter for different marketing channels (Organic, Paid, Social).
• Tracking regional performance: View sales revenue by month for various sales territories or countries.
• Segmenting product categories: Compare the number of units sold for different product lines over a year-to-date period.
• Evaluating team performance: Display the number of closed-won deals per month for each salesperson.

In each of these cases, the goal is to see not just the overall trend, but how that trend plays out across different segments. Using a single cluttered chart makes this kind of comparison difficult, while individual charts for each segment would lose the benefit of a standardized, easy-to-scan overview.

How to Create a Small Multiples Chart in Power BI (Step-by-Step)

Creating your first small multiples visual is surprisingly simple. Power BI integrates this feature directly into several native chart types, including bar, column, line, and area charts. Let’s walk through building one from scratch using a sample sales dataset.

Imagine we have sales data and we want to see monthly revenue broken down by product category.

Step 1: Choose a Compatible Chart

Start by adding a new visual to your report canvas. For this example, a Clustered column chart or a Line chart would work perfectly. Let's go with a line chart, as it's great for showing trends over time.

Step 2: Add Your Core Data Fields

Next, you’ll set up the primary structure of your chart just as you normally would. Drag and drop your fields into the Visualizations pane:

• Drag your time-based field (e.g., Order Date) to the X-axis field well.
• Drag your numerical measure (e.g., Sales Revenue) to the Y-axis field well.

At this point, you'll have a single line chart showing total sales revenue over time. It's a useful start, but it doesn't tell a very detailed story.

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Step 3: Add Your Category to the Small Multiples Field

Here’s where the magic happens. Find the categorical field you want to use to split your chart. In our example, this is the Product Category field.

Drag your Product Category field and drop it into the Small multiple field well in the Visualizations pane. This field well appears just below the Y-axis field.

Instantly, Power BI transforms your single line chart into a convenient grid of charts, one for each product category! Your canvas will now show separate trend lines for "Electronics," "Home Goods," "Apparel," and any other categories in your data, all perfectly aligned for easy comparison.

Customizing and Formatting Your Small Multiples

Now that you've created your visual, you can customize its appearance to make it even more readable and professional. All formatting options are found in the Format your visual tab of the Visualizations pane.

Adjusting the Grid Layout

By default, Power BI arranges your charts into a 2x2 grid and adds scroll bars if there are more categories. You can change this to suit your dashboard design.

1. Select your small multiples visual.
2. Go to the Format visual section.
3. Expand the Small multiples section.
4. Under Grid layout, you can manually set the number of Rows and Columns.

This allows you to control how many charts are visible at once, which is great for fitting the visual neatly onto your report page. For instance, if you have six categories, you might set it to a 2x3 or 3x2 grid to show them all without scrolling.

Formatting Titles and Borders

Clear titles are essential for knowing which chart represents which category.

• In that same Small multiple formatting section, you can customize the Title for each mini-chart. Adjust the font, color, background, and position (Top, Bottom) to match your report’s style.
• Just below, you'll find options for Gridlines and Padding to add visual separation and space between your charts, improving overall readability. You can also add borders around each multiple under the Border dropdown to create distinct boxes.

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Controlling the Y-Axis Scale

This is one of the most important formatting options. By default, Power BI uses a shared y-axis scale for all multiples, meaning the minimum and maximum values on the y-axis are the same for every chart. This is a foundational best practice for accurate, apples-to-apples comparison.

However, there may be times where one category has values drastically different from the others (e.g., one product category generates millions in sales while others generate thousands). In such cases, the trends in the smaller categories can be flattened and difficult to see. To address this:

1. Navigate to the Y-axis formatting options.
2. Scroll down and find the Shared y-axis toggle.

Turning this toggle off gives each mini-chart its own y-axis scale, better highlighting the trend within that specific category. Be cautious with this setting—while it shows individual trends more clearly, it makes direct visual comparison of magnitudes between charts misleading.

Pro Tips for Designing Effective Small Multiples

• Don't Overcomplicate: The beauty of small multiples lies in their simplicity. Avoid adding too many additional dimensions, legends, or data points to the individual mini-charts. Let the comparison across charts do the heavy lifting.
• Sensible Sorting: The order of your multiples matters. By default, they are sorted alphabetically by category name. Consider sorting them by a key metric (e.g., highest to lowest total sales) to draw immediate attention to top or bottom performers. You can control this by adjusting the sort order of the chart visual itself.
• Limit the Quantity: Just because you can, doesn't mean you should. A grid of 50 tiny charts is just as overwhelming as one chart with 50 tangled lines. Aim for a reasonable number that fits comfortably on one screen without extensive scrolling. If you have too many categories, consider filtering to the top 10 or grouping smaller categories into an "Other" segment.
• Make Them Interactive: Combine small multiples with slicers and filters. For example, add a slicer for "Year" or "Region" to allow users to dynamically explore the data and drill down into the insights that matter most to them.

Final Thoughts

Small multiples are a powerful yet underutilized feature in Power BI that transform cluttered visualizations into clear, comparable insights. By breaking down your data across categories, they allow for quick and easy pattern recognition. They are perfect for comparing trends over time, tracking performance by segment, and telling a much more nuanced story with your data.

Learning visualization techniques like this in Power BI is time well spent, but building reports from scratch can still feel like a grind, especially when you're connecting to data from a dozen different apps. At my company, we built Graphed because we wanted to turn that hours-long reporting process into a 30-second conversation. Instead of manually configuring charts and wrestling with BI tools, you can just describe the dashboard you want in plain English, and our AI builds it instantly, pulling live data from all your marketing and sales sources.