Export data to Google BigQuery
Zoho DataPrep supports exporting data to Google BigQuery. BigQuery is a fully managed enterprise data warehouse that helps you manage organization data.
To export data to Google BigQuery
1. Open an existing pipeline or create a pipeline from the Home Page, Pipelines tab or Workspaces tab. You can bring your data from 50+sources.
2. On the Pipeline Builder page, once you have completed creating your data flow and applying the necessary transforms in your stages, you can right-click a stage and select the Add Destination option.
2. Choose
Google BigQuery
under the
All destinations
tab or from the
Cloud databases
category.
3.
Select an account from the saved connections or add a new account using the
Add new
option.
4. Enter the Project ID and click the
Sign in with Google
button.
4.
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 will be saved for exporting to Google BigQuery project in the future. Credentials are securely encrypted and stored.
5. Click
Connect.
6. Once you have successfully connected to your Google BigQuery project, you can choose when and where to export the data.
7. Choose
Existing table
if you want to export data to an existing table and select one from the list of tables available in the database. There are two ways in which you can choose how to add the new rows to the table.
- If the new rows are to be added to the table, choose Append.
- If the newly added rows are to replace the existing rows, select Overwrite from the dropdown.
8. If you want to create a new table, select the
New table
option and give a name to your table in the field below.
9. Click Next. Now that you have added a destination, you may want to 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
Info: Each run is saved as a job. When a pipeline run is executed, the data fetched from your data sources will be prepared using the series of transforms you have applied in each of the stages, and then data will be exported to your destination. This complete process is captured in the Jobs page.
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