One of the visualization types available in Power BI is the "Filled Map," which enables you to display data on maps using various geographic boundaries such as countries, regions, or custom polygons.

While the Filled Map is a valuable feature, it's essential to be aware of its limitations to use it effectively.

In this blog post, I'll explore the limitations of Power BI's Filled Map and provide insights into how to work around them.

Power BI Filled Map Limitations

Data Granularity:

One of the primary limitations of the Power BI Filled Map is related to data granularity. The Filled Map visualizes data at a higher level of aggregation, such as country or region boundaries. This means that if your dataset contains more granular location data (e.g., city-level data), the Filled Map might not provide the level of detail you need.

Solution:

• Consider aggregating your data to match the granularity of the Filled Map visualization. For example, you can group city-level data into regions or countries to align with the available map boundaries.

Limited Geographic Boundaries:

Power BI's Filled Map is dependent on predefined geographic boundaries, such as country or region borders. This limitation means that some regions or areas might not be available in the default map visualization.

Solution:

• Check if your desired geographic boundaries are supported in the Filled Map. If not, you may need to use custom polygons or look for alternative visualization types like Shape Maps.

Custom Boundaries Complexity:

While Power BI allows users to create custom polygons for more detailed geographical visualizations, creating and maintaining custom boundaries can be a complex task, especially for large datasets or dynamically changing geographies.

Solution:

• If you need to work with custom boundaries, ensure that your data source is consistently updated to reflect any changes in geographic boundaries.
• Consider using third-party tools or services to simplify the process of creating and managing custom polygons for your visualizations.

Performance:

The performance of the Filled Map visual can be affected by the size and complexity of your dataset. Large datasets with numerous data points can lead to slower rendering times and potential performance issues.

Solution:

• Optimize your dataset by removing unnecessary columns and rows to reduce the data volume.
• Use filters and slicers to allow users to interactively explore the data, limiting the amount of data displayed at once.

Limited Customization:

Power BI's Filled Map offers limited customization options compared to other visualization types. Users may find it challenging to customize the appearance and behavior of the map to suit their specific needs.

Solution:

• Explore other visualization types like ArcGIS Maps for Power BI or custom visuals that offer more extensive customization options.
• Provide additional context and information through text boxes, tooltips, or other visuals to complement the Filled Map.

Conclusion

The Power BI Filled Map is a useful tool for visualizing data on geographic boundaries, but it has its limitations.

Understanding these limitations and knowing how to work around them is crucial for creating effective and informative reports and dashboards.

By carefully considering your data granularity, geographic boundaries, and performance needs, you can make the most of the Filled Map visualization in Power BI while addressing its inherent constraints.

Additionally, exploring alternative visualization options can help you overcome specific limitations and create compelling data-driven presentations.