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

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 article explains how to create a library for BigQuery in SAS and create 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.

Getting Started

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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, register an application to obtain the OAuth JWT values.

In addition to the OAuth values, 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
InitiateOAuth = GETANDREFRESH

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. 👁 Creating a library for BigQuery in SAS.
   

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. 👁 Selecting table(s) to visualize.
   
3. Select columns and right-click to add filtering, ordering, grouping, etc. 👁 Selecting columns(s) to visualize and configuring the query.
   
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. 👁 Create a local view to work with BigQuery data.
   

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;
   

   👁 A simple BigQuery data report.
   

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;
   

   👁 A simple BigQuery data chart.