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  1. Preface
  2. Part 1: Introduction to Google BigQuery connectors
  3. Part 2: Data Integration with Google BigQuery V2 Connector
  4. Part 3: Data Integration with Google BigQuery Connector

Google BigQuery Connectors

Google BigQuery Connectors

Read from Google Cloud Storage and write to Google BigQuery

Read from Google Cloud Storage and write to Google BigQuery

You can configure
SQL ELT optimization
for a mapping that uses a Google Cloud Storage connection in the Source transformation to read from Google Cloud Storage and a Google BigQuery V2 connection in the Target transformation to write to Google BigQuery.

Example

You work for a rapidly growing data science organization. Your organization develops software products to analyze financials, building financial graphs connecting people profiles, companies, jobs, advertisers, and publishers. The organization uses infrastructure based on Google Cloud Platform and stores its data in Google Cloud Storage files. The organization plans to implement a business intelligence service to build visualization and perform real-time analysis. You can load data from Google Cloud Storage to Google BigQuery by configuring the transformations to support the adequate data warehouse model and the consuming requirements.
Create an Google Cloud Storage V2 connection to read data form the Google Cloud Storage source. Create an Google BigQuery V2 connection and use
SQL ELT optimization
to write data to the Google BigQuery target to enhance the performance and reduce the cost involved.

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