Explore Geographical Relationhips in BigQuery Data with Power Map

The CData ODBC Driver for GoogleBigQuery is easy to set up and use with self-service analytics solutions like Power BI: Microsoft Excel provides built-in support for the ODBC standard. This article shows how to load the current BigQuery data into Excel and start generating location-based insights on BigQuery data in Power Map.

Create an ODBC Data Source for GoogleBigQuery

To connect to BigQuery data, your application will use connection properties defined in the data source name (DSN).

Below is a typical connection string:

DataSetId=MyDataSetId;ProjectId=MyProjectId;

You can configure the DSN in the built-in Microsoft ODBC Data Source Administrator. This is the last step of the driver installation. See the "Getting Started" chapter in the help documentation for a guide to use the Microsoft ODBC Data Source Administrator to create and configure a DSN for BigQuery data.

Import BigQuery Data into Excel

You can import data into Power Map either from an Excel spreadsheet or from Power Pivot. For a step-by-step guide to use either method to import BigQuery data, see the "Using the ODBC Driver" section in the help documentation.

Geocode BigQuery Data

After importing the BigQuery data into an Excel spreadsheet or into PowerPivot, you can drag and drop BigQuery entities in Power Map. To open Power Map, click any cell in the spreadsheet and click Insert -> Map.

In the Choose Geography menu, Power Map detects the columns that have geographic information. In the Geography and Map Level menu in the Layer Pane, you can select the columns you want to work with. Power Map then plots the data. A dot represents a record that has this value. When you have selected the geographic columns you want, click Next.

Select Measures and Categories

You can then simply select columns: Measures and categories are automatically detected. The available chart types are Stacked Column, Clustered Column, Bubble, Heat Map, and Region.