A Sankey diagram has become a popular tool in the recent past. In most cases, the tool is mainly used to depict data flow from one set of values to the next. The aspects being connected to one another are called nodes, while the connections are known as links. A Sankey plays a crucial role, especially when you want to display many to many data mapping in different scenarios.
If you intend to showcase a bunch of data stages, the Sankey diagram has your back covered. Google Analytics is one of the major platforms using this technique to showcase traffic flow from one page to the next. However, there is another category of Sankey diagrams that you need to know, given that it plays a crucial role in data visualization.
Suppose you have a massive data set you need to visualize and generate insights. In that case, you need to adopt a more advanced methodology that can easily evaluate the data into bits and generate easy-to-read results. Even though a Sankey diagram can get this job done, you need a more advanced version with multiple features. This is where the multi-level Sankey diagram comes in!
Multi-Level Sankey Diagram
This is an advanced version of a Sankey diagram which you can easily generate from a standard Sankey diagram without experiencing any challenge. The design of this diagram seems to be similar to that of a typical Sankey diagram, although it has many calculated fields. You must copy the sheets, adjust and calculate the tables and incorporate them into the data dashboard.
However, if it’s your first time creating a multi-level Sankey diagram, this may seem a complicated exercise since you need to grasp the technical aspects used to execute the task. Besides, you can make a multi-level Sankey diagram as appealing as possible. On most occasions, the diagram comes with bold colors, which you can easily change depending on your preference.
Most people always prefer completing the diagram at the fifth level. However, you can still add more layers to the diagram depending on the size of the data you intend to display to your viewers.
Traceable Multi-Level Sankey
The traceable multi-level Sankey falls in the class of multi-level Sankey diagrams mainly used to present a general idea about the entire data. Remember that there is no a straightforward way that you can use to trace records across the entire data. You need to implement a unique approach to crawl across the data values and generate results.
Traceable multi-level operates at an aggregate level, enabling it to combine a detailed data report that can be used to analyze the general idea presented with the data values. Also, it is always good to trace one item at a time within your data. This will, in turn, generate a more concise report that you can use to draw insights from your data.
When using this diagram, you will realize that every data record on the diagram is separate from the other. Every section of your present data can be accessed directly by clicking on the drop-down menu. In addition, once you select a particular item on the chart, you will realize that it has been highlighted using a different color.
If you decide to hover on a specific bar within the chart, you will realize that the entire flow is automatically highlighted. Contrary, if you hover on the entire flow, it will only highlight individual flows within the diagram. These features are mainly meant to give you an exact test of all the sections of the data you are dealing with.
With the traceable multi-level Sankey, you can monitor the nature of your data and get a rough view of the hidden insights that readers need to know during data analysis.
Applications of a Multi-Level Sankey Diagram
Data analytics utilizes a multi-level Sankey diagram to detect the effectiveness of campaigns running across different platforms. Initially, a lot of guesswork and assumptions were applied to detect how far the campaigns have gone and their general performance. This aspect has been eliminated by the use of Sankey diagrams.
This technique has been dramatically adopted within the finance sector to detect cash flow and finance-related products. Remember that finance is a crucial sector that requires strict monitoring to avoid losses. Sankey diagrams are used to monitor how cash moves from one section to the other.
The health sector has also adopted the use of a multi-level Sankey diagram in monitoring the journey taken by patients before they recover. This methodology generates a comprehensive report from the consultation point until the patient marks the end of the treatment journey.
Benefits of a Multi-Level Sankey Diagram
A multi-level Sankey diagram comes with multiple benefits, especially when every aspect has been executed perfectly. It offers an exceptional level of viewing data from different perspectives since it has the power to drill down to granular data insights or uncover specific details regarding the data.
With the aid of different viewpoints, data professionals can easily shed light on the essential data elements and generate interactive views for the respective market audience. Also, it saves time since you don’t need to spend the whole day working on your data because the Sankey nails directly on the data that matters to your business.
In addition, you can use a multi-level Sankey diagram to compose prolific data posts, making your work stand out from the rest. Also, it gives you a better opportunity to analyze the number of customers who have viewed the post and how many have liked it. Those customers who like the post may go ahead and read the comments and add them to the cart.
If you realize that most of your customers tend to add products to your cart and abandon them, you need to make a quick data analysis to identify why this is happening. A multi-level Sankey diagram can be applied in the process to visualize the challenges experienced by customers. You will then utilize the data report to work on the areas that need adjustment to secure the well-being of your business.
A multi-level Sankey diagram can be used in different scenarios across the industries. You can easily customize the diagram and make it perfectly fit the amount of data you intend to data visualize and draw conclusions from it. However, you should understand the number of levels that you need to generate from the data to make the presentation easier.