Im currently creating some POC reports with mobile report publisher for my manager and so far ive used various charts and graphs and had drill throughs etc which all work fine.
I would like to demo a map report either using the Range Stop heat map or the Gradient heat map for the UK but im really unsure as to what data i need for it and in what format.
For example the data properties for the Range stop heat map are labelled Keys: Values: Targets but i dont know what kind of information i should have in a query in order to populate the map properly. I work for a housing association so was hoping i could just do something with a property ref and postcode but it doesnt seem to recognise this data.
For your scenario, I'd like to recommend you to use more detail location information to instead.
In the dataset: tips to improve the underlying dataset
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. If you are live connectig to SQL Server Analysis Services, you will need to set the data categorization outside of Power BI using SQL Server Data Tools (SSDT).
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.
For example, 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.
Make sure when each field only has the specific information tied to the categorization. For example, your City location field should be Southampton, not Southampton, New York. And Address location fields should be 1 Microsoft Way and not 1 Microsoft Way, Redmond, WA.
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.
4. Use Place category for columns with full location information
While we encourage you to use geo-hierarchies in your maps, if you must use a single location column with full geographical information, you can set the data categorization to Place. For example, if the data in your column is full addresses, such as 1 Microsoft Way, Redmond Washington 98052, this generalized data category will work best with Bing.
For your scenario, I'd like to recommend you to use more detail location information to instead.
In the dataset: tips to improve the underlying dataset
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. If you are live connectig to SQL Server Analysis Services, you will need to set the data categorization outside of Power BI using SQL Server Data Tools (SSDT).
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.
For example, 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.
Make sure when each field only has the specific information tied to the categorization. For example, your City location field should be Southampton, not Southampton, New York. And Address location fields should be 1 Microsoft Way and not 1 Microsoft Way, Redmond, WA.
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.
4. Use Place category for columns with full location information
While we encourage you to use geo-hierarchies in your maps, if you must use a single location column with full geographical information, you can set the data categorization to Place. For example, if the data in your column is full addresses, such as 1 Microsoft Way, Redmond Washington 98052, this generalized data category will work best with Bing.
