How to load data from TrustPilot to BigQuery

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

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Bespoke pipelines are:
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Furthermore, you will need to build and maintain Y x Z pipelines with Y sources and Z destinations to cover all your needs.
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Start syncing with Airbyte in 3 easy steps within 10 minutes

Set up a TrustPilot 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 TrustPilot 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 TrustPilot 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.
Try Airbyte CloudManual method (the hard way)

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Check out our interactive demo and our how-to videos to learn how you can sync data from any source to any destination.

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Raman Singh

Tech Lead at Symend

Predictable, straightforward pricing model that simplified budgeting and significantly reduced overall spend

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Chase Zieman

Chief Data Officer

“Airbyte helped us accelerate our progress by years, compared to our competitors. We don’t need to worry about connectors and focus on creating value for our users instead of building infrastructure. That’s priceless. The time and energy saved allows us to disrupt and grow faster.”

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Rupak Patel

Operational Intelligence Manager

"With Airbyte, we could just push a few buttons, allow API access, and bring all the data into Google BigQuery. By blending all the different marketing data sources, we can gain valuable insights."

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How to Sync to Manually

Step 1: Understand Trustpilot APIs

Begin by familiarizing yourself with Trustpilot's API documentation. Trustpilot provides several APIs that allow you to extract data. You'll need to obtain an API key by creating a Trustpilot business account and registering an application to access these APIs.

Write a script in a programming language of your choice (Python is commonly used for such tasks) to extract data from Trustpilot using their APIs. Use HTTP requests to fetch the data, and ensure you handle pagination if Trustpilot limits the number of results per request.

Once data is extracted, transform it into a format suitable for BigQuery. CSV or JSON formats are typically used. Ensure that your data structure aligns with the schema you plan to use in BigQuery, making necessary transformations to match data types and field names.

Set up a Google Cloud account if you don’t have one. Create a new project in Google Cloud Console, and enable the BigQuery API. Ensure that you have the necessary permissions and billing set up to use BigQuery.

Before loading data into BigQuery, upload it to Google Cloud Storage (GCS). Use the `gsutil` command-line tool or Google Cloud Console to create a bucket and upload your CSV or JSON files. Ensure the files are named appropriately for easy identification.

Use the BigQuery Console, `bq` command-line tool, or a custom script to load data from Google Cloud Storage into BigQuery. Create a dataset and table in BigQuery that matches your data schema, and execute the load job. Monitor the job for any errors and ensure data is correctly loaded.

To keep your BigQuery data updated, automate the entire process. Use a cron job or a cloud function to schedule regular data extraction and loading. Ensure your script handles exceptions and logs errors for troubleshooting. This will help maintain data consistency and integrity over time.

By following these steps, you can effectively move data from Trustpilot to BigQuery without relying on third-party connectors or integrations.