Visualizing Data Flows: How to Create Sankey Charts with Astrato Analytics

Data storytelling is an integral part of modern business intelligence, providing insights that drive decision-making. Visualizations like Sankey charts are a powerful tool for this, as they not only convey information efficiently but also reveal the underlying narrative of data flows and relationships. Inspired by the renowned Tableau expert, Andy Kriebel, I’ve embarked on a journey to adapt his insightful techniques for Sankey chart creation to the unique environment of Astrato Analytics.

Why Sankey Charts?

Sankey charts are distinctive for their ability to map out and measure flows between different nodes, representing quantities with varying thicknesses. These charts excel at illustrating complex networks—such as supply chains, website traffic paths, or even budget allocations—making them an invaluable resource in the data visualization toolkit.

Adapting to Astrato Analytics

Leveraging Astrato’s seamless integration with leading data platforms like Snowflake, Databricks, Dremio, and Google Cloud, I’ve distilled the process of creating a Sankey chart into four straightforward steps. This approach not only simplifies the creation process but also utilizes the robust, pushdown SQL capabilities of Astrato Analytics to handle complex data operations efficiently.

The Four-Step Approach

1. Add a Measure

Begin by selecting the appropriate measure that will act as the weight for the flows in your Sankey chart. This could be financial figures, quantities, or any other metric that’s central to your analysis.

2. Add Dimensions

Dimensions are the nodes between which the flow is measured. In Astrato, you can easily drag and drop these dimensions into your chart, organizing them in a way that tells the best story.

3. Generate AI Title

Use Astrato’s AI capabilities to automatically suggest a chart title that is both descriptive and informative, encapsulating the essence of your data story.

4. Style & Done!

Finally, apply the finishing touches to your chart with Astrato’s styling options. Choose color palettes and designs that make your chart not only informative but also visually appealing.

Concluding Reflections

In an effort to foster a collaborative and knowledge-sharing community, I warmly invite you to contribute your experiences and ideas. Have the steps outlined been instrumental in your endeavors with Sankey charts? Furthermore, are there other types of visualizations for which you’re eager to find tutorials? Your constructive feedback is crucial, as it will inform our future content, ensuring it remains pertinent and beneficial to our audience.

Moreover, I wholeheartedly encourage data enthusiasts to delve into the rich capabilities offered by Astrato Analytics. It’s more than mere chart construction—it’s about weaving compelling data stories that engage and inspire action.

For additional tips, deeper insights, and lively discussions about expanding the horizons of data visualization within the modern data stack, I recommend visiting astrato.io. Remember, a Sankey chart isn’t just a visual tool; it’s a profound way to illustrate the dynamics of data flow and interconnections. The variation in the flow’s thickness is not just a design choice—it symbolizes the quantity of flow, simplifying the understanding of data distribution and bringing clarity to complex information.

Here are some useful links for further reading

• Sankey use cases: https://astrato.io/blog/sankey-use-cases/
• Astrato documentation: https://help.astrato.io/en/articles/8904548-sankey-chart
• Great resource by DataVizProject: https://datavizproject.com/data-type/sankey-diagram/#:~:text=Sankey%20diagrams%20are%20a%20specific,accounts%20on%20a%20community%20level.