Import data from Google BigQuery

Zoho DataPrep supports importing data from Google BigQuery. BigQuery is a fully managed enterprise data warehouse that helps you manage organization data.

To import data from Google BigQuery

1. Create a pipeline or open an existing pipeline from the Home Page, Pipelines tab or Workspaces tab and click the Add data option. You can also click the Import data option under the Workspaces tab to import data.

Info: You can also click the Import data

icon at the top of the pipeline builder and bring data from multiple sources into the pipeline.

2. Choose the Cloud databases category from the left pane and click Google BigQuery. You can also directly search the option in the search box.

3. Select an account from the saved data connections, or add a new account using the Add new option.

4. To add a new connection, enter the Project ID and click the Sign in with Google button.

Note: Project ID can be found on your Google cloud console. Google BigQuery authorizes access to resources based on verified identity.

5. After signing in with your google account, you can click Continue to allow Zoho DataPrep to access data from your Google BigQuery project for the first time.

Note: The connection configuration is securely saved for importing data from the Google BigQuery project in the future.

6. Select the tables that need to be imported. Click Import.

7. You can also use SQL query to select and import data.

8. Click Import to begin importing data from your Google BigQuery project.

9. Once you import data successfully, it will take you to the Pipeline builder page where you can start applying transforms. You can also right-click the stage and choose the Prepare data option to prepare your data in the DataPrep Studio page. Click here to know about transforms.

10. Once you are done creating your data flow and applying necessary transforms in your stages, you can right-click a stage and add a destination to complete your data flow.

Note: After adding a destination to the pipeline, you can try executing your pipeline using a manual run at first. Once you make sure manual run works, you can then set up schedule to automate the pipeline. Learn about the different types of runs here.

SEE ALSO

How to add a new dataset?

Schedule data import

Export data to Google BigQuery

How to import data from saved data connections?

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