Warehouses and Lakes
Finance & Ops Analytics

How to load data from GoCardless to BigQuery

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

TL;DR

This can be done by building a data pipeline manually, usually a Python script (you can leverage a tool as Apache Airflow for this). This process can take more than a full week of development. Or it can be done in minutes on Airbyte in three easy steps:

  1. set up GoCardless as a source connector (using Auth, or usually an API key)
  2. set up BigQuery as a destination connector
  3. define which data you want to transfer and how frequently

You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud.

This tutorial’s purpose is to show you how.

What is GoCardless

Gocardless is an online tool that collects direct bank payments on behalf of other businesses and It was founded in January 2011. GoCardless is an online Direct Debit supplier with a secure set-up process that permits the customer to pay both easily and safely. We ask all our customers to sign up to gain a streamlined payment procedure whereby the amount is automatically debited from the account provided every month. GoCardless is aims at becoming the world's bank payment network.

What is BigQuery

BigQuery is an enterprise data warehouse that draws on the processing power of Google Cloud Storage to enable fast processing of SQL queries through massive datasets. BigQuery helps businesses select the most appropriate software provider to assemble their data, based on the platforms the business uses. Once a business’ data is acculumated, it is moved into BigQuery. The company controls access to the data, but BigQuery stores and processes it for greater speed and convenience.

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Prerequisites

  1. A GoCardless account to transfer your customer data automatically from.
  2. A BigQuery account.
  3. An active Airbyte Cloud account, or you can also choose to use Airbyte Open Source locally. You can follow the instructions to set up Airbyte on your system using docker-compose.

Airbyte is an open-source data integration platform that consolidates and streamlines the process of extracting and loading data from multiple data sources to data warehouses. It offers pre-built connectors, including GoCardless and BigQuery, for seamless data migration.

When using Airbyte to move data from GoCardless to BigQuery, it extracts data from GoCardless using the source connector, converts it into a format BigQuery can ingest using the provided schema, and then loads it into BigQuery via the destination connector. This allows businesses to leverage their GoCardless data for advanced analytics and insights within BigQuery, simplifying the ETL process and saving significant time and resources.

Step 1: Set up GoCardless as a source connector

1. First, navigate to the GoCardless source connector page on Airbyte.com.
2. Click on the "Add Source" button to begin the process of adding your GoCardless credentials.
3. In the "Connection Configuration" section, enter your GoCardless access token. This can be found in your GoCardless account under "Developers" > "Personal Access Tokens".
4. Next, enter the webhook secret. This can also be found in your GoCardless account under "Developers" > "Webhooks".
5. In the "Sync Schema" section, select the tables you want to sync data from.
6. Click on the "Test" button to ensure that your credentials are correct and that Airbyte can connect to your GoCardless account.
7. If the test is successful, click on the "Create" button to save your GoCardless source connector.
8. You can now use this connector to sync data from your GoCardless account to your destination of choice.  

Note: It is important to ensure that your GoCardless account has the necessary permissions to allow Airbyte to access your data. You may need to adjust your account settings to grant these permissions.

Step 2: Set up BigQuery as a destination connector

1. First, navigate to the Airbyte dashboard and select the "Destinations" tab on the left-hand side of the screen.

2. Scroll down until you find the "BigQuery" destination connector and click on it.

3. Click the "Create Destination" button to begin setting up your BigQuery destination.

4. Enter your Google Cloud Platform project ID and service account credentials in the appropriate fields.

5. Next, select the dataset you want to use for your destination and enter the table prefix you want to use.

6. Choose the schema mapping for your data, which will determine how your data is organized in BigQuery.

7. Finally, review your settings and click the "Create Destination" button to complete the setup process.

8. Once your destination is created, you can begin configuring your source connectors to start syncing data to BigQuery.

9. To do this, navigate to the "Sources" tab on the left-hand side of the screen and select the source connector you want to use.

10. Follow the prompts to enter your source credentials and configure your sync settings.

11. When you reach the "Destination" step, select your BigQuery destination from the dropdown menu and choose the dataset and table prefix you want to use.

12. Review your settings and click the "Create Connection" button to start syncing data from your source to your BigQuery destination.

Step 3: Set up a connection to sync your GoCardless data to BigQuery

Once you've successfully connected GoCardless as a data source and BigQuery as a destination in Airbyte, you can set up a data pipeline between them with the following steps:

  1. Create a new connection: On the Airbyte dashboard, navigate to the 'Connections' tab and click the '+ New Connection' button.
  2. Choose your source: Select GoCardless from the dropdown list of your configured sources.
  3. Select your destination: Choose BigQuery from the dropdown list of your configured destinations.
  4. Configure your sync: Define the frequency of your data syncs based on your business needs. Airbyte allows both manual and automatic scheduling for your data refreshes.
  5. Select the data to sync: Choose the specific GoCardless objects you want to import data from towards BigQuery. You can sync all data or select specific tables and fields.
  6. Select the sync mode for your streams: Choose between full refreshes or incremental syncs (with deduplication if you want), and this for all streams or at the stream level. Incremental is only available for streams that have a primary cursor.
  7. Test your connection: Click the 'Test Connection' button to make sure that your setup works. If the connection test is successful, save your configuration.
  8. Start the sync: If the test passes, click 'Set Up Connection'. Airbyte will start moving data from GoCardless to BigQuery according to your settings.

Remember, Airbyte keeps your data in sync at the frequency you determine, ensuring your BigQuery data warehouse is always up-to-date with your GoCardless data.

Use Cases to transfer your GoCardless data to BigQuery

Integrating data from GoCardless to BigQuery provides several benefits. Here are a few use cases:

  1. Advanced Analytics: BigQuery’s powerful data processing capabilities enable you to perform complex queries and data analysis on your GoCardless data, extracting insights that wouldn't be possible within GoCardless alone.
  2. Data Consolidation: If you're using multiple other sources along with GoCardless, syncing to BigQuery allows you to centralize your data for a holistic view of your operations, and to set up a change data capture process so you never have any discrepancies in your data again.
  3. Historical Data Analysis: GoCardless has limits on historical data. Syncing data to BigQuery allows for long-term data retention and analysis of historical trends over time.
  4. Data Security and Compliance: BigQuery provides robust data security features. Syncing GoCardless data to BigQuery ensures your data is secured and allows for advanced data governance and compliance management.
  5. Scalability: BigQuery can handle large volumes of data without affecting performance, providing an ideal solution for growing businesses with expanding GoCardless data.
  6. Data Science and Machine Learning: By having GoCardless data in BigQuery, you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
  7. Reporting and Visualization: While GoCardless provides reporting tools, data visualization tools like Tableau, PowerBI, Looker (Google Data Studio) can connect to BigQuery, providing more advanced business intelligence options. If you have a GoCardless table that needs to be converted to a BigQuery table, Airbyte can do that automatically.

Wrapping Up

To summarize, this tutorial has shown you how to:

  1. Configure a GoCardless account as an Airbyte data source connector.
  2. Configure BigQuery as a data destination connector.
  3. Create an Airbyte data pipeline that will automatically be moving data directly from GoCardless to BigQuery after you set a schedule

With Airbyte, creating data pipelines take minutes, and the data integration possibilities are endless. Airbyte supports the largest catalog of API tools, databases, and files, among other sources. Airbyte's connectors are open-source, so you can add any custom objects to the connector, or even build a new connector from scratch without any local dev environment or any data engineer within 10 minutes with the no-code connector builder.

We look forward to seeing you make use of it! We invite you to join the conversation on our community Slack Channel, or sign up for our newsletter. You should also check out other Airbyte tutorials, and Airbyte’s content hub!

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Connectors Used

Frequently Asked Questions

What data can you extract from GoCardless?

GoCardless's API provides access to a wide range of data related to payments and customers. The following are the categories of data that can be accessed through the API:

1. Payment data: This includes information about payments made by customers, such as the amount, currency, status, and date of payment.  
2. Customer data: This includes information about customers, such as their name, email address, phone number, and billing address.  
3. Subscription data: This includes information about subscriptions, such as the amount, frequency, and start and end dates.  
4. Mandate data: This includes information about mandates, which are the authorizations given by customers to allow GoCardless to collect payments from their bank accounts.  
5. Bank account data: This includes information about the bank accounts used by customers to make payments, such as the account number, sort code, and bank name.  
6. Refund data: This includes information about refunds issued to customers, such as the amount, currency, and date of refund.  
7. Dispute data: This includes information about disputes raised by customers, such as the reason for the dispute and the status of the dispute resolution process.

Overall, GoCardless's API provides comprehensive access to data related to payments and customers, enabling businesses to manage their payment processes more efficiently and effectively.

What data can you transfer to BigQuery?

You can transfer a wide variety of data to BigQuery. This usually includes structured, semi-structured, and unstructured data like transaction records, log files, JSON data, CSV files, and more, allowing robust, scalable data integration and analysis.

What are top ETL tools to transfer data from GoCardless to BigQuery?

The most prominent ETL tools to transfer data from GoCardless to BigQuery include:

  • Airbyte
  • Fivetran
  • Stitch
  • Matillion
  • Talend Data Integration

These tools help in extracting data from GoCardless and various sources (APIs, databases, and more), transforming it efficiently, and loading it into BigQuery and other databases, data warehouses and data lakes, enhancing data management capabilities.