Building a Power BI Heatmap Simplified: 2 Easy Steps

on BI Tool, Data Virtualization Tools, Data Visualization, Power BI • March 4th, 2022 • Write for Hevo

Power BI Heatmap_FI

Data Analytics and Business Intelligence tools that assist organizations in making effective data-driven decisions are constantly evolving like never before. Power BI is one such BI (Business Intelligence) tool that helps organizations conduct an informative analysis of their business and customer data in order to gain actionable insights. Power BI offers a ton of Data Analytics and Visualization features that enable users to create informative Dashboards or Reports and use them to make data-driven decisions. You can easily combine data from various sources and turn it into valuable insights. Power BI Heatmap is one of the most popular visualizations used by data professionals to depict distributed networks, advertisement impact, and so on.

Upon a complete walkthrough of this article, you will gain a decent understanding of Power BI Heatmaps and how they can be leveraged for Data Visualization. You will also learn about the steps required to create Power BI Heatmaps in a seamless manner. Read along!

Table of Contents

What is Power BI?

Power BI
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Microsoft Power BI is one of the most popular Business Intelligence tools that analyzes and visualizes raw data to present actionable information. It integrates Business Analytics, Data Visualization, and best practices to assist organizations in making data-driven decisions. Power BI provides Cloud-based services for interactive visualizations, as well as an easy-to-use interface for end-users to create their own Reports and Dashboards. You can leverage it to extract data from various Cloud and On-premise systems and build Dashboards that track the most important metrics for you and your business. Apple, Exxon Mobil, Walmart, and Toyota Motor North America are some of the prominent names that leverage Microsoft Power BI for Business Intelligence.

Key Features of Microsoft Power BI

Some of the key features of Power BI are as follows:

  • Data Selection: Power BI enables you to filter your datasets to focus on small but highly relevant datasets first. This enables you to pay attention to individual data in the dataset rather than the complete dataset at once.
  • Responsiveness: Accessing presentations and reports on mobile phones can sometimes hinder responsiveness. However, Power BI allows you to view enlarged Navigation Trees on both iOS and Android platforms. You can zoom in or out of the Reports or Graphs to make sure that all of the information is visible.
  • Seamless Functionalities: Power BI includes drag-and-drop functionality that allows you to quickly create customized reports. It also allows you to delve deeper into the data visualizations to better understand the data. Natural Language Queries eliminate the need for users to spend time on learning a complex query language.
  • Data Connectivity: Power BI houses support for various connectors that integrate with the Cloud data. This allows businesses to easily view metrics or visuals. The data source is directly integrated via the connector and once the connector successfully retrieves the data, you can create some interactive visuals to identify trends and patterns.

Understanding Power BI Heatmaps for Data Visualization

As the name implies, a Heatmap is a type of visualization that is used to project the density of data on a map for any given point. A Power BI Heatmap is a type of visualization that demonstrates the density of data on a map. It is a graphical representation of data in which individual values in a matrix are represented as colors.

Since most businesses deal with structured data, a Heatmap is a powerful tool for cross-examining multivariate data by placing variables in rows and columns where you can Color-Highlight important data containing cells within the table. This is accomplished by highlighting behavioral data with a Warm-to-Cool Color Spectrum. Categorical data is color-coded, but numerical data requires a color scale that blends from one color to the next to show the difference between high and low values.

Power BI Heatmaps are useful for displaying variation across multiple variables, revealing patterns, indicating whether variables are analogous to one another, and determining whether there are any relationships between them. Power BI Heatmaps also provides comprehensive information about an entity or a data point based on certain variables in the dataset. 

Applications of Heatmaps in Organizations

Some of the ways in which an organization can leverage Heatmaps in Power BI Dashboards are as follows:

  • Heatmaps can be used by businesses to find new locations for distribution or service centers. Companies can map the locations from which they can provide efficient services to the maximum number of customers by analyzing customer density using color patches.
  • You can easily identify the locations to run your marketing campaigns and reach out to relevant customers by mapping the data sets gathered from various websites. You can, for example, use demographic data to determine where the majority of your target customers live and when they are most likely to see your campaigns.
  • Demographic Heatmaps can also be used to identify areas where a business can expand and open a new franchise to maximize profit. Using radius analysis, one can create customer clusters within the expected area surrounding their new franchise.
  • Heatmaps are also relevant to the Sports Industry. At times, in a cricket match, you might have seen a Heatmap demonstrating favorite zones of a batter to play a shot and similarly showing what are the lines where bowlers are getting maximum wickets.

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How to Create a Power BI Heatmap?

For the purpose of this tutorial, let us create a Power BI Heatmap representing the population of European Countries. You can access the dataset from here and we’ll suggest you to copy this data to an Excel Sheet.

Step 1: Load the Data

  • Open Power BI and click on the Get Data option.
  • Now, select the desired format for the input file. For this tutorial, we are going to use Excel for loading the data.
  • Select the desired Excel File for loading the data.
Required Excel Sheet
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Step 2: Import Custom Visualizations

Since Power BI does not offer an in-built Heatmap component, you’ll need to use custom visualizations to create the Power BI Heatmap. Follow the steps given below to do so:

  • Navigate to the Visualizations Panel and click on the three dots.
  • Now, select the Import from Marketplace option.
  • Search for Heatmap and add it.
Adding Heatmap
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  • Now, drag the custom visual Heatmap component into the Power BI Design Panel.
  • Drag and drop the Country field to the Location field (ID).
  • Drag and drop the Population field to Value.
  • Change the Renderer Format type to Heat, you can find it under the Format Properties of Heatmap.
  • As a result, our population heatmap of European countries will look the following:
Power BI Heatmap
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One interesting thing to notice about this Power BI Heatmap is that the legend, which represents the value ranges, is located at the top of the heatmap.

Things to remember while using Power BI Heatmaps

There are some key pointers you should keep in mind while creating Heatmaps in Power BI. Some of them are as follows:

  • Power BI Heatmaps are customized visualizations that can only be accessed via Power BI Marketplace.
  • Power BI Marketplace has a variety of visualization charts that are rarely used. The visualization section is the only place where you’ll find common charts.
  • While creating a Heatmap, always choose a color that represents heat or density.
  • Heatmap only deals with numbers.

Conclusion

This blog introduced you to Power BI along with its key features. You also learned about how Power BI Heatmaps can be leveraged for Data Visualization. Furthermore, this article highlighted the steps required to create a Power BI Heatmap.

As you collect and manage your data across several applications and databases in your business, it is important to consolidate it for a complete performance analysis of your business. To achieve this you need to assign a portion of your engineering bandwidth to Integrate data from all sources, Clean & Transform it, and finally, Load it to a Cloud Data Warehouse, BI Tool like Power BI, or a destination of your choice for further Business Analytics. All of these challenges can be comfortably solved by a Cloud-based ETL tool such as Hevo Data.  

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Share your experience of learning about Power BI Heatmaps in the comments below!

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