Hierarchical axis for cartesian charts in Power BI is a powerful tool for visualizing complex data relationships and uncovering hidden insights. By breaking down data into smaller, more manageable chunks, it becomes easier to understand the overall picture and identify patterns and trends that may be hidden in the overall data. Also, by creating different levels of granularity, we can view data in a variety of ways depending on our specific needs, which allows you to make more informed decisions. With the help of hierarchical axis in Power BI, we can gain a deeper understanding of our data and make more informed decisions that will help drive our business forward.
Annual Salary by Country
Data visualization is a crucial part of the data analysis process. A picture is worth a thousand words, and with the right visualization, data analysts and BI consultants can quickly identify trends and patterns in large datasets that would be difficult to spot with just raw data.
The hierarchical axis in Microsoft Power BI is a powerful tool that helps data analysts and BI consultants to view data in a hierarchical manner. This feature allows you to group data into multiple levels and view the data at different levels of detail. It is a useful tool for working with data that has a natural hierarchy, such as dates, regions, departments, or product categories. This allows you to better visualize and understand complex data relationships.
HIERARCHICAL AXIS FOR CARTESIAN CHART
Displaying data on a chart using hierarchical format means that you can group data by multiple levels, such as by category and subcategory, and display the data in a nested format. For example, in a bar chart, the top level of the hierarchy might be represented by the highest level of categories, with each category broken down into subcategories represented by smaller bars within the larger bar.
We have Employees annual salary, country, city, and department data. We want to make a cartesian chart by grouping country, city and department. The top level of the hierarchy will be the country, such as “Brazil”, “China” and "United States ". Within each country, there are different city, such as "Rio de Janerio", "Sao Paulo", "Beijing", "Shanghai", "Chicago", etc. And within each city, there are different department.
Using a hierarchical axis, you could create a bar chart that displays the average of employee’s annual salary for each country on the top level, and within each country bar, displays the average of employee’s annual salary for each city as smaller bars. And within each city bar, displays the average of employee’s annual salary for each department as even smaller bars.
This would allow us to quickly see which countries, cities, and departments have the highest average of employee’s annual salary, and which ones have the lowest.
It could be visualized in the following way:
A large bar for "Brazil" representing the average of employee’s annual salary from that country.
Within the "Brazil" bar, smaller bars for "Rio de Janerio", "Sao Paulo", etc representing the average of employee’s annual salary from each city.
And within each city bar, even smaller bars for departments representing the average of employee’s annual salary from each department.
This is just one example of how we can use a hierarchical axis to display data in a more meaningful and intuitive way in Power BI. To use it in Power BI, we can simply put the data that we want to be grouped in X or Y-Axis in Data Visualization by order that we want.
Here are the benefits of using a hierarchical axis:
Improved data comprehension: By breaking down data into smaller, more manageable chunks, it becomes easier to understand the overall picture.
More accurate data analysis: With a hierarchical axis, we can drill down into different levels of data, which allows us to identify patterns and trends that may be hidden in the overall data.
Greater flexibility in visualizing data: With a hierarchical axis, we can create different levels of granularity, which allows us to view data in a variety of ways depending on your specific needs.
Better comparison: With a hierarchical axis, we can compare different levels of data in a way that's not possible with a flat chart.
Effective utilization of space: By using a nested format, we can show more information in a smaller area than a flat chart.
Overall, using a hierarchical axis in Power BI enables the user to make the most of the data and to analyze it in a way that suits their needs. By using this feature, we can gain a deeper understanding of our data and make more informed decisions which makes it easier to make data-driven decisions.
You can see more details about Hierarchical axis in this link.
Need assistance with your PowerBI implementation? Contact us today!