Power BI Insights: Geospatial data; Asymmetrical columns; Calculation Groups

Power BI pros share tips on processing geospatial data, asymmetrical columns, and Calculation Groups.

Analyzing geospatial data with Data Explorer, Dynamic M and Power BI

Chris Webb took a look at how to analyze geospatial data with Power BI, Dynamic M, and Azure Data Explorer. In his example, he imagined a scenario in which a chain of supermarkets tries to determine what other stores are close to its location. Starting with Retail Points data from Geolytix, Webb loaded a CSV file into ADX and put together a  KQL query to filter the list of supermarkets. He then created two M parameters called selectedradius and selectedstore binding them to two other tables in the dataset with dynamic M parameters.

For now, not many people are using Azure Data Explorer as a data source for Power BI, but the approach offers a different way to demo the power of dynamic M parameters.

Creating a matrix with asymmetrical columns and rows in Power BI

FREE Membership Required to View Full Content:

Become a MemberLogin

Joining MSDynamicsWorld.com gives you free, unlimited access to news, analysis, white papers, case studies, product brochures, and more. You can also receive periodic email newsletters with the latest relevant articles and content updates. 
Learn more about us here