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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.
CData simplifies access and integration of live Google BigQuery data. Our customers leverage CData connectivity to:
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
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.
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 .
π Modify the query in the SQL Editor.With the query defined, you are ready to work with BigQuery data in Alteryx Designer.
π The configured Data Input tool, complete with query.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.
Thanks to built-in, high-performance data processing, you will be able to quickly cleanse, transform, and/or analyze your BigQuery data with Alteryx.
Download a free trial of the Google BigQuery ODBC Driver to get started:
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π Google BigQuery IconThe 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.