A Pareto chart is a powerful visualization that combines both bar and line charts to identify the most significant factors in a dataset. Named after the Pareto principle (also known as the 80/20 rule), it helps users focus on the causes that generate the majority of results. In this article, we’ll walk through how to build a Pareto chart in Power BI using the Superstore dataset, a common sample dataset used in data visualization training.

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What Is a Pareto Chart?

A Pareto chart typically:

• Shows individual values in descending order as bars (e.g., sales by category).
• Shows cumulative percentage of the total on a secondary line chart.

It is often used to identify the top contributors to a result—e.g., which few customers generate most of the sales, or which few products are responsible for most complaints.

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Dataset: Superstore Sample

The Superstore dataset contains transactional data including:

• Customer Name
• Product Name
• Category and Sub-Category
• Sales, Profit, Quantity
• Region, State, City
• Order Date

You can download this dataset in Excel or CSV format from multiple sources online. In Power BI, load the dataset by choosing Home > Get Data > Excel and selecting the relevant sheet.

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Step-by-Step Guide

Step 1: Load the Superstore Dataset

• Open Power BI Desktop
• Click Home > Get Data > Excel
• Choose your Superstore file and import the dataset (usually named Orders)

Step 2: Create a Bar Chart with Customer Sales

1. Insert a bar chart or clustered column chart.
2. Drag Sub-Category to the X-axis.
3. Drag Sales to the Y-axis.
4. Sort by Sales descending.

Step 3: Create a Measure for Total Sales

Go to Modeling > New Measure, and create:

Total Sales = SUM(Orders[Sales])

Step 4: Create a Measure for Cumulative Sales

Now create a cumulative sum based on the Sub-Category ranking:

Cumulative Sales = 
VAR CurrentRank = RANKX(
    ALL('Orders'[Sub-Category]),
    [Total Sales],
    ,
    DESC,
    Dense
)
RETURN
CALCULATE(
    [Total Sales],
    FILTER(
        ALL('Orders'[Sub-Category]),
        RANKX(ALL('Orders'[Sub-Category]), [Total Sales], , DESC, Dense) <= CurrentRank
    )
)

Step 5: Create Cumulative Sales Percentage Measure

Now, calculate the % of cumulative vs. total:

Cumulative Sales % = 
DIVIDE(
    [Cumulative Sales],
    CALCULATE([Total Sales], ALL('Orders'[Sub-Category]))
)

Step 6: Convert to Pareto Chart Using Dual Axis

1. Change the chart to Line and Clustered Column Chart visual.
2. Set up the following:
   • Shared Axis: Sub-Category
   • Column y-Axis Values: Total Sales
   • Line y-Axis Values: Cumulative Sales %
3. Sort by Total Sales in descending order.

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Customize Your Pareto Chart

• Format the line chart to show percentage (under Data labels > Display units = Percentage).
• Enable data labels on both bars and lines.
• Adjust color for better contrast between bars and line.
• Add a reference line at 80% to highlight Pareto threshold

You will now see:

• Bars: Total sales by sub-category, descending
• First line: Cumulative % climbing from 0% to 100%
• Second line: Flat 80% across the chart
• You can now visually identify the sub-category at which cumulative % crosses 80%

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Tips and Best Practices

Tip	Recommendation
Use RANKX	RANKX is crucial for accurate cumulative calculations
Use ALLSELECTED	Keeps slicers functional when building visuals
Show % on Axis	Makes cumulative line easier to interpret
Add 80% Line	Makes the “Pareto point” visually obvious
Use Dual Axis	Combine line and bar cleanly with correct proportions

Pareto charts are a great way to derive actionable insights from your data using Power BI. With just a few DAX measures and the Line and Clustered Column Chart, you can clearly visualize top contributors and make data-driven decisions.