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Sankey diagrams are powerful tools in Power BI for visualizing flows and connections between categories. Whether you want to track website traffic, visualize financial flows, or understand complex systems, Sankey charts bring clarity to your data.
Named after the Irish engineer Matthew Henry Phineas Riall Sankey, this type of diagram uses arrows or links of varying widths to represent the magnitude of flows, making it easy to identify major contributions and bottlenecks.
In Power BI, creating a Sankey Diagram Power BI allows users to transform complex data sets into clear and intuitive visuals, aiding in better decision-making and insight generation.
In this guide, you’ll learn how to create, customize, and troubleshoot Sankey diagrams in Power BI without coding or confusion!
Let’s dive right in.
Definition: A Sankey Diagram in Power BI is a type of data visualization showing a data flow from multiple source levels to multiple destination levels. It is also known as the Sankey Chart Power BI.
They are used in advanced analytics.
The Sankey Chart is a type of data visualization in Power BI that allows you to show an entire process, including all the stages and their interrelatedness.
It is also easy to see the most significant contributor to the data flow.
A good example of this in Power BI for Mac is a chart depicting user flow data through a website. Most users begin at the landing page, visit other pages, and finally drop off.
Key Features of Power BI Sankey Diagrams:
Now that we know what Power BI Sankey Diagrams are, let’s delve into some best-case scenarios to understand how to use the Power BI Sankey Diagram.
An example of this use case is visualizing customers’ journeys. This helps companies understand how customers interact with products and services and with the brand in general.
Businesses with repeat customers, for example, would benefit from creating Sankey Charts in Power BI. The Netflix marketing team, for instance, might want to map their customers’ viewing journeys.
They can make use of information from their predictive algorithm. To make the data even more beneficial, they can group it based on customer demographics.
This would help them craft more relatable marketing messages, for example.
An example of hierarchical data is the mapping of revenue based on region. The Netflix sales team, for example, can map its revenue by region.
The region with the highest revenue would be the biggest contributor. Eventually, they can rank the data based on width (representing the revenue per region).
The links with the greatest widths will be ranked first.
A Microsoft Power BI Sankey Chart visualizes how a company’s budget is distributed across different departments or projects, highlighting areas of overspending or underspending.
It tracks how visitors flow through a website, showing where they drop off or continue, helping to optimize user experience and conversion rates.
The Sankey chart shows how different types of energy are consumed across various processes in a factory, helping to identify inefficiencies and areas for energy savings.
It visualizes the customer journey, showing how users move through different stages (e.g., from awareness to purchase), helping businesses optimize their marketing and sales strategies.
Use Sankey diagrams to visually map the flow of materials, information, and costs across your supply chain. Easily spot inefficiencies, bottlenecks, and areas for optimization. Sankey charts simplify complex supply chain dynamics into an intuitive, easy-to-read format.
Here is the complete comparison of the Sankey Diagram in Power BI and other charts:
| Chart Type | Purpose/Use | Strengths | Weaknesses |
| Sankey Diagram | Visualizes flows between stages or categories, showing proportionate volumes. | Great for tracking complex processes, resource movement, and highlighting major paths. | Not ideal for time-series data or precise value comparisons. |
| Multi-Axis Line Chart | Tracks multiple variables over time, each with its scale. | Excellent for showing trends, patterns, and relationships between different metrics. | It can become cluttered if too many axes or lines are added. |
| Comparison Chart | Compares discrete values across categories (e.g., bar or column charts). | Simple, fast comparison of categories; very easy to read. | Doesn’t show flow or relationships between categories. |
| Likert Chart | Displays survey results or ratings across a range of agreement or satisfaction levels. | Perfect for showing the distribution of opinions or satisfaction ratings. | Limited use beyond survey data; less effective for flow or time-based trends. |
2. Example
| Source | Target | Value |
| Supplier A | Warehouse | 1000 |
| Warehouse | Store X | 600 |
| Warehouse | Store Y | 400 |
✔ Unique Nodes – No duplicates in Source & Target.
✔ No Loops – Avoid circular flows (A → B → A).
✔ Numeric Values – Only positive numbers in Value.
Now that we know what makes a Sankey Chart effective, let’s learn how to create one.
A good example of this chart can be the flow of your annual business expense report. This way, you can see your biggest expenses, which will be your biggest contributors.
There are several ways to create this Diagram:
We will focus on creating Sankey Charts within Power BI. You don’t require any programming knowledge to create a Sankey Diagram with Power BI.
You can create your Sankey within a very short time and adjust it as needed.
There are a few options when creating Sankey Diagrams within Power BI:
We’ll look at drawing Sankey Charts in Power BI with the first two steps, step by step.
Let’s learn how to create Sankey Diagrams in Power BI using Power BI services. We will divide the steps into several steps.
You need to have Power BI Desktop installed on your computer to use this option. We will divide the steps into several stages.
You are all set to go and present your newly created Sankey Diagram in Power BI to your audience. Next, let’s look at some frequently asked questions.
Ready to try it? Download Sankey Diagram for Power BI now!
The following video will help you create a Sankey Chart in Microsoft Power BI.
What makes a Power BI Sankey Chart Model effective?
Ensure your dataset includes at least:
Mistake: The width of the flows may not always reflect their actual proportion, leading to misleading visual representations of data.
Solution: Ensure that flow widths are directly proportional to the values they represent. Double-check the data input to confirm accuracy, and use Power BI’s built-in tools to align flow sizes properly.
Mistake: Including too many categories or data points can clutter the Sankey diagram, making it difficult to interpret the information effectively.
Solution: Limit the number of flows and nodes to the most critical elements. Group related data together, or break it down into multiple diagrams if necessary, to improve clarity and focus.
Mistake: Without clear and descriptive labels, it can be hard for viewers to understand the flow relationships and key data points.
Solution: Add concise and meaningful labels to all flows and nodes. Utilize Power BI’s text boxes and formatting options to enhance readability and provide context.
Mistake: Not taking advantage of Power BI’s interactive capabilities can limit the diagram’s usefulness and engagement.
Solution: Implement tooltips, drill-through actions, and slicers to allow users to explore the data interactively. This provides deeper insights and enhances the user experience.
Mistake: Using too many colors or poorly contrasting colors can make the diagram hard to read and visually overwhelming.
Solution: Stick to a consistent color scheme with high contrast for clarity. Use Power BI’s color palette options to highlight key flows or categories without overcomplicating the design.
Sankey charts with multiple levels provide an intuitive visual representation of how values flow across different stages or categories, helping users easily trace complex relationships. For example, tracking the movement of customers from awareness to purchase or monitoring resource allocation across departments.
These charts are great at clearly highlighting where the flow diminishes. By showing where values or quantities drop off, such as in a conversion funnel, it becomes easy to pinpoint problem areas or inefficiencies. This is particularly useful for analyzing sales pipelines, customer retention, or process workflows.
With multiple levels, the Sankey chart transforms raw data into a compelling narrative, allowing users to track the flow of information across several dimensions. For instance, you can track how a product moves through different regions, then through sales channels, and ultimately into revenue generation. It effectively builds a story about the data.
Sankey charts are highly interactive. Users can hover over the links to view detailed tooltips and even filter other visuals based on the selections they make within the chart. This encourages users to explore data more deeply and discover insights that may otherwise go unnoticed, making the report more engaging.
With a clear flow of values across multiple stages, stakeholders can easily assess how well various elements of their business are performing. For example, a marketing team can analyze the movement of customers from lead generation to conversion, allowing for data-driven decision-making. This insight can then be used to optimize resource allocation or adjust marketing strategies for better performance.
A Sankey Graph Power BI can become less effective if there are too many categories or data points. Overcrowding the chart with multiple levels or sources can make it difficult to interpret and lead to visual clutter. It’s best used with a moderate number of flows to maintain clarity.
When dealing with large datasets, Microsoft Power BI Sankey Charts can experience performance slowdowns. The complexity of rendering multiple connections and flows between categories can lead to sluggish interactions, especially in real-time dashboards with high-frequency updates.
While Sankey charts are effective at showing the flow of values, they may not provide enough granular details. The tooltips can be useful, but they might not always suffice when users require specific, detailed data without hovering over each flow or node.
In Sankey charts, the width of the flow lines represents value sizes, but when flows are very close in magnitude, it becomes hard to visually distinguish between them. This can lead to difficulty in comparing flows of similar size, especially when the chart is dense with data.
Compared to other visualizations, Sankey charts in Power BI have limited interactivity options and customization features. While users can filter based on nodes, the ability to dynamically adjust or manipulate the flow representation is somewhat restricted.
>>Check out our Sankey Diagram Custom Templates in Power BI
You need to ensure that you have only one row for every entry. For example, you should only have one entry per region if you are showing regional data.
Yes, you can create a Sankey diagram in Power BI by using custom visuals available from the Microsoft AppSource marketplace. Once imported, you can map your source, destination, and weight fields to easily visualize flows between categories.
Yes, you can make a flow chart in Power BI by using custom visuals like the Flow Map or by creatively arranging shapes and connectors in a report. Some users also use Sankey diagrams or Visio integration for more advanced flowchart designs.
Using the right tool for data visualization helps you get your message across to your audience. Sankey charts are your best option for presenting data flows.
We have explored the world of Power BI Sankey Diagrams in depth. We began by defining Sankey Charts and their components (nodes, links, and drop-offs).
We then looked at some best-case scenarios where you can use these Diagrams. Sankey Charts can be used when looking for patterns over time. They are also handy when working with hierarchical data.
We discussed some factors that determine what an effective Sankey Chart is. These include simplicity, width, and storytelling. The most important takeaways are:
Ultimately, we learned how to create Sankey charts, step by step. We looked at making Sankey Charts with Power BI Web Service. We also discussed drawing Sankey Diagrams with Power BI Desktop.
We answered a few frequently asked questions related to Sankey Charts, too. We tackled the data used in these Diagrams and the history behind their origins.
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