How to load data from GoCardless to BigQuery

Learn how to use Airbyte to synchronize your GoCardless data into BigQuery within minutes.

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Start syncing with Airbyte in 3 easy steps within 10 minutes

Set up a GoCardless connector in Airbyte

Connect to or one of 400+ pre-built or 10,000+ custom connectors through simple account authentication.

Set up BigQuery for your extracted GoCardless data

Select where you want to import data from your source to. You can also choose other cloud data warehouses, databases, data lakes, vector databases, or any other supported Airbyte destinations.

Configure the GoCardless to BigQuery in Airbyte

This includes selecting the data you want to extract - streams and columns -, the sync frequency, where in the destination you want that data to be loaded.
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How to Sync to Manually

Step 1: Export Data from GoCardless

Begin by logging into your GoCardless dashboard. Use the export feature to download the necessary data as a CSV file. GoCardless typically allows you to export various data, such as payments, customers, and mandates. Ensure that you export the data in a format that contains all the fields you need for analysis in BigQuery.

Once downloaded, open the CSV files in a spreadsheet application like Microsoft Excel or Google Sheets. Clean and format the data if necessary. This may include removing unnecessary columns, standardizing date formats, or ensuring there are no empty rows. Save the cleaned data as a CSV file, which will be ready for upload to BigQuery.

Navigate to the Google Cloud Console and set up a new project if you don't already have one. Ensure that the BigQuery API is enabled for your project. This is a necessary step for managing and querying your datasets within BigQuery.

In the Google Cloud Console, go to the BigQuery section. Create a new dataset within your project. A dataset is a container that holds your tables, and you can create it by clicking on "Create Dataset" and filling in the required details such as dataset ID, data location, and any expiration settings.

Within the BigQuery interface, select your newly created dataset. Click on "Create Table" and choose the "Upload" option. Select your prepared CSV file from local storage. Specify the file format as CSV. Configure the schema by either allowing BigQuery to auto-detect or by manually entering the field names and types if your data requires specific configurations.

During the upload process, ensure you review the schema settings. Double-check that data types are correctly interpreted (e.g., INTEGER, STRING, DATE). Set any additional table options such as partitioning or clustering, which can help optimize query performance.

Once the data is uploaded, run a few sample queries to verify that the data was imported correctly. You can use the BigQuery query editor to write SQL queries that check data integrity and perform basic analysis. Ensure everything is working as expected and that the data matches what you exported from GoCardless.

By following these steps, you can manually transfer data from GoCardless to BigQuery without using third-party connectors or integrations.