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Create data visualizations with BigQuery data in Power Map.
The CData ODBC Driver for BigQuery 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.
About BigQuery Data Integration
CData simplifies access and integration of live Google BigQuery data. Our customers leverage CData connectivity to:
- Simplify access to BigQuery with broad out-of-the-box support for authentication schemes, including OAuth, OAuth JWT, and GCP Instance.
- Enhance data workflows with Bi-directional data access between BigQuery and other applications.
- Perform key BigQuery actions like starting, retrieving, and canceling jobs; deleting tables; or insert job loads through SQL stored procedures.
Most CData customers are using Google BigQuery as their data warehouse and so use CData solutions to migrate business data from separate sources into BigQuery for comprehensive analytics. Other customers use our connectivity to analyze and report on their Google BigQuery data, with many customers using both solutions.
For more details on how CData enhances your Google BigQuery experience, check out our blog post: https://www.cdata.com/blog/what-is-bigquery
Getting Started
Create an ODBC Data Source for BigQuery
If you have not already, first specify connection properties in an ODBC DSN (data source name). This is the last step of the driver installation. You can use the Microsoft ODBC Data Source Administrator to create and configure ODBC DSNs.
Google uses the OAuth authentication standard. To access Google APIs on behalf of individual users, you can use the embedded credentials or you can register your own OAuth app.
OAuth also enables you to use a service account to connect on behalf of users in a Google Apps domain. To authenticate with a service account, you will need to register an application to obtain the OAuth JWT values.
In addition to the OAuth values, you will need to specify the DatasetId and ProjectId. See the "Getting Started" chapter of the help documentation for a guide to using OAuth.
When you configure the DSN, you may also want to set the Max Rows connection property. This will limit the number of rows returned, which is especially helpful for improving performance when designing reports and visualizations.
When you configure the DSN, you may also want to set the Max Rows connection property. This will limit the number of rows returned, which is especially helpful for improving performance when designing reports and visualizations.
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.
