Use the CData ODBC Driver for BigQuery in SAS for Real-Time Reporting and Analytics



Connect to real-time BigQuery data in SAS for reporting, analytics, and visualizations using the CData ODBC Driver for BigQuery.

SAS is a software suite developed for advanced analytics, multivariate analysis, business intelligence, data management, and predictive analytics. When you pair SAS with the CData ODBC Driver for BigQuery, you gain database-like access to live BigQuery data from SAS, expanding your reporting and analytics capabilities. This articles walks through creating a library for BigQuery in SAS and creating a simple report based on real-time BigQuery data.

The CData ODBC Driver offers unmatched performance for interacting with live BigQuery data in SAS due to optimized data processing built into the driver. When you issue complex SQL queries from SAS to BigQuery, the driver pushes supported SQL operations, like filters and aggregations, directly to BigQuery and utilizes the embedded SQL engine to process unsupported operations (often SQL functions and JOIN operations) client-side. With built-in dynamic metadata querying, you can easily visualize and analyze BigQuery data in SAS.

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


Connect to BigQuery as an ODBC Data Source

Information for connecting to BigQuery follows, along with different instructions for configuring a DSN in Windows and Linux environments (the ODBC Driver for BigQuery must be installed on the machine hosting the SAS System).

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.

Windows

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.

Linux

If you are installing the CData ODBC Driver for BigQuery in a Linux environment, the driver installation predefines a system DSN. You can modify the DSN by editing the system data sources file (/etc/odbc.ini) and defining the required connection properties.

/etc/odbc.ini

[CData GoogleBigQuery Sys] Driver = CData ODBC Driver for BigQuery Description = My Description DataSetId = MyDataSetId ProjectId = MyProjectId

For specific information on using these configuration files, please refer to the help documentation (installed and found online).

Create a BigQuery Library in SAS

Connect to BigQuery in SAS by adding a library based on the CData ODBC Driver for BigQuery.

  1. Open SAS and expand Libraries in the Explorer pane.
  2. In the Active Libraries window, right-click and select New.
  3. Name your library (odbclib), select ODBC as the Engine, and click to Enable at startup (if you want the library to persist between sessions).
  4. Set Data Source to the DSN you previously configured and click OK.

Create a View from a BigQuery Query

SAS natively supports querying data either using a low-code, point-and-click Query tool or programmatically with PROC SQL and a custom SQL query. When you create a View in SAS, the defining query is executed each time the view is queried. This means that you always query live BigQuery data for reports, charts, and analytics.

Using the Query Tool

  1. In SAS, click Tools -> Query
  2. Select the table sources and the table(s) you wish to pull data from. Then, click OK.
  3. Select columns and right-click to add filtering, ordering, grouping, etc.
  4. Create a local view to contain the query results by right-clicking the SQL Query Tool window, selecting Show Query, and clicking Create View. Name the View and click OK.

Using PROC SQL

  1. In SAS, navigate to the Editor window.
  2. Use PROC SQL to query the data and create a local view.
    NOTE: This procedure creates a view in the Work library. You can optionally specify a library in the create view statement.
    proc sql;
      create view orders_view as
      select 
        ordername, 
        freight 
      from 
        odbclib.orders 
      where 
        ShipCity = 'New York';
    quit;
    
  3. Click Run -> Submit to execute the query and create a local view.

Report On or Visualize BigQuery Data in SAS

With a local view created, you can report, visualize, or otherwise analyze BigQuery data using the powerful SAS features. Print a simple report using PROC PRINT and create a basic graph based on the data using PROC GCHART.

Print an HTML Report

  1. In SAS, navigate to the Editor window.
  2. Use PROC PRINT to print an HTML report for the BigQuery Orders data.
    proc print data=orders;
      title "BigQuery Orders Data";
    run;
    

Print a Chart

  1. In SAS, navigate to the Editor window.
  2. Use PROC GCHART to create a chart for the Orders data.
    proc gchart data=orders;
      pie ordername / sumvar=freight
          value=arrow
          percent=arrow
          noheading
          percent=inside plabel=(height=12pt)
          slice=inside value=none
          name='OrdersChart';
    run;
    

Ready to get started?

Download a free trial of the Google BigQuery ODBC Driver to get started:

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Learn more:

Google BigQuery Icon Google BigQuery ODBC Driver

The Google BigQuery ODBC Driver is a powerful tool that allows you to connect with live Google BigQuery data, directly from any applications that support ODBC connectivity.

Access Google BigQuery like you would a database - read, write, and update Datasets, Tables, etc. through a standard ODBC Driver interface.