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How to build a SQL Server Analysis Service Tabular Model from BigQuery data using CData drivers.
SQL Server Analysis Services (SSAS) is an analytical data engine used in decision support and business analytics. It provides enterprise-grade semantic data models for business reports and client applications, such as Power BI, Excel, Reporting Services reports, and other data visualization tools. When paired with the CData ODBC Driver for Google BigQuery, you can create a tabular model from BigQuery data for deeper and faster data analysis.
Create a Connection to BigQuery Data
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.
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
Creating a Data Source for BigQuery
Start by creating a new Analysis Services Tabular Project in Visual Studio. Next create a Data Source for BigQuery in the project.
- In the Tabular Model Explorer, right-click Data Sources and select "New Data Source"
- Select "ODBC" from the Other tab and click "Connect"
- Select the DSN you previously configured
- Choose "Default or Custom" as the authentication option and click "Connect"
Add Tables & Relationships
After creating the data source you are ready to import tables and define the relationships between the tables.
- Right-click the new data source, click "Import New Tables" and select the tables to import
- After importing the tables, right-click "Relationships" and click "Create Relationships"
- Select table(s), and choose the foreign keys, cardinality, and filter direction
Create Measures
After importing the tables and defining the relationships, you are ready to create measures.
- Select the column in the table for which you wish to create a measure
- In the Extensions menu -> click "Columns" -> "AutoSum" and select your aggregation method
Deploy the Model
Once you create measures, you are ready to deploy the model. Configure the target server and database by right-clicking the project found in the Solution Explorer and selecting "Properties." Configure the "Deployment Server" properties and click "OK."

After configuring the deployment server, open the "Build" menu and click "Deploy Solution." You now have a tabular model for BigQuery data in your SSAS instance, ready to be analyzed, reported, and viewed. Get started with a free, 30-day trial of the CData ODBC Driver for Google BigQuery.