Prepare, Blend, and Analyze BigQuery Data in Alteryx Designer

The CData ODBC Driver for BigQuery enables access to live data from BigQuery under the ODBC standard, allowing you work with BigQuery data in a wide variety of BI, reporting, and ETL tools and directly, using familiar SQL queries. This article shows how to connect to BigQuery data using an ODBC connection in Alteryx Designer to perform self-service BI, data preparation, data blending, and advanced analytics.

The CData ODBC drivers offer unmatched performance for interacting with live BigQuery data in Alteryx Designer due to optimized data processing built into the driver. When you issue complex SQL queries from Alteryx Designer 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 visualize and analyze BigQuery data using native Alteryx data field types.

Connect to BigQuery Data

1. If you have not already done so, provide values for the required connection properties in the data source name (DSN). You can configure the DSN using the built-in Microsoft ODBC Data Source Administrator. This is also the last step of the driver installation. See the "Getting Started" chapter in the Help documentation for a guide to using the Microsoft ODBC Data Source Administrator to create and configure a DSN.
   
   

   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.

2. Open Alteryx Designer and create a new workflow.
3. Drag and drop a new input data tool onto the workflow.
4. Click the drop down under Connect a File or Database and select the Data sources tab.
5. Navigate tot he end of the page and click on "ODBC" under "Generic connection"
6. Select the DSN (CData BigQuery Source) that you configured for use in Alteryx.
7. In the wizard that opens, drag, and drop the table to be queried in the "Query Builder box." Select the fields by checking the boxes that you wish to include in your query. Where possible, the complex queries generated by the filters and aggregations will be pushed down to BigQuery, while any unsupported operations (which can include SQL functions and JOIN operations) will be managed client-side by the CData SQL engine embedded in the connector.

If you wish to further customize your dataset, you can open the SQL Editor and modify the query manually, adding clauses, aggregations, and other operations to ensure that you are retrieving exactly the BigQuery data you want .

With the query defined, you are ready to work with BigQuery data in Alteryx Designer.

Perform Self-Service Analytics on BigQuery Data

You are now ready to create a workflow to prepare, blend, and analyze BigQuery data. The CData ODBC Driver performs dynamic metadata discovery, presenting data using Alteryx data field types and allowing you to leverage the Designer's tools to manipulate data as needed and build meaningful datasets. In the example below, you will cleanse and browse data.

1. Add a data cleansing tool to the workflow and check the boxes in Replace Nulls to replace null text fields with blanks and replace null numeric fields with 0. You can also check the box in Remove Unwanted Characters to remove leading and trailing whitespace.
2. Add a browse data tool to the workflow.
3. Click to run the workflow (CTRL+R).
4. Browse your cleansed BigQuery data in the results view.

Thanks to built-in, high-performance data processing, you will be able to quickly cleanse, transform, and/or analyze your BigQuery data with Alteryx.