Power BI integrates with Bing Maps to provide default map coordinates (a process called geo-coding) so you can create maps. Together they use algorithms to identify the correct location, but sometimes it's a best guess. If Power BI tries can't create the map visualization on its own, it enlists the help of Bing Maps.
To increase the likelihood of correct geo-coding, use the following tips. The first set of tips is for you to use if you have access to the dataset itself. And the second set of tips is things you can do in Power BI if you don't have access to the dataset.
Power BI service and Power BI Desktop send Bing the geo data it needs to create the map visualization. This may include the data in the Location, Latitude, and Longitude buckets and geo fields in any of the Report level, Page level, or Visual level filter buckets. Exactly what is sent varies by map type. To learn more, see Bing Maps privacy.
Filled maps require a field in the Location bucket; even if latitude and longitude are provided. Whatever data is in the Location, Latitude, or Longitude buckets is sent to Bing.
In the example below, the field Vendor is being used for geo-coding, so all vendor data is sent to Bing. Data from the Size and Color saturation buckets is not sent to Bing.
In this second example below, the field Territory is being used for geo-coding, so all territory data is sent to Bing. Data from the Legend and Color saturation buckets is not sent to Bing.
If you have access to the dataset that is being used to create the map visualization, there are a few things you can do to increase the likelihood of correct geo-coding.
1. Categorize geographic fields in Power BI Desktop
In Power BI Desktop, you can ensure fields are correctly geo-coded by setting the Data Category on the data fields. Select the desired table, go to the Advanced ribbon and then set the Data Category to Address, City, Continent, Country/Region, Country, Postal Code, State or Province. These data categories help Bing correctly encode the date. To learn more, see Data categorization in Power BI Desktop.
2. Use more than one location column.
Sometimes, even setting the data categories for mapping isn't enough for Bing to correctly guess your intent. Some designations are ambiguous because the location exists in multiple countries or regions. For example, there's a Southampton in England, Pennsylvania, and New York.
Power BI uses Bing's unstructured URL template service to get the latitude and longitude coordinates based on a set of address values for any country. If your data doesn't contain enough location data, add those columns and categorize them appropriately.
If you only have a City column, Bing may have a hard time geo-coding. Add additional geo columns to make the location unambiguous. Sometimes all it takes is adding one more location column to the dataset - in this case state/province. And don't forget to categorize it properly, see #1 above.
3. Use specific Latitude and Longitude
Add latitude and longitude values to your dataset. This removes any ambiguity and returns results more quickly. Latitude and Longitude fields must be in Decimal Number format, which you can set in the data model.
1. Use latitude and longitude fields (if they exist)
In Power BI, if the dataset you are using has fields for longitude and latitude -- use them! Power BI has special buckets to help make the map data unambiguous. Just drag the field that contains your latitude data into the Visualizations > Latitude area. And do the same for your longitude data. When you do this, you also need to fill the Location field when creating your visualizations. Otherwise, the data is aggregated by default, so for example, the latitude and longitude would be paired at the state level, not the city level.
When your dataset already has different levels of location data, you and your colleagues can use Power BI to create geo-hierarchies. To do this, drag more than one field into the Location bucket. Used together in this way, the fields become a geo-hierarchy. In the example below we have added geo fields for: Country/Region, State, and City. In Power BI you and your colleagues can drill up and down using this geo-hierarchy.
More questions? Try the Power BI Community