How to load data from Intercom to BigQuery

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

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Start syncing with Airbyte in 3 easy steps within 10 minutes

Set up a Intercom 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 Intercom 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 Intercom 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 Intercom

Begin by exporting the necessary data from Intercom. Log into your Intercom account and navigate to the section containing the data you wish to export, such as users, conversations, or companies. Use Intercom’s built-in export functionality to download the data as CSV or JSON files. This will serve as the raw data source for transfer to BigQuery.

Once you have your exported files, you need to prepare them for import into BigQuery. Ensure that your data is clean and formatted correctly. If your data is in CSV format, check that it uses a consistent delimiter and handle any special characters properly. If using JSON, ensure the data is properly structured and validated.

To facilitate the transfer, create a Google Cloud Storage (GCS) bucket. Log into your Google Cloud Platform (GCP) account, go to the Google Cloud Storage section, and create a new bucket. This bucket will temporarily store your Intercom data files before they are loaded into BigQuery. Ensure the bucket has the appropriate permissions set to allow data uploads.

With your GCS bucket ready, upload the prepared CSV or JSON files from your local machine to the bucket. You can do this using the GCP Console web interface or the `gsutil` command-line tool. For `gsutil`, a command would look like `gsutil cp path/to/local/file.csv gs://your-bucket-name/`.

Before importing data, create a dataset and table in BigQuery to hold your Intercom data. Navigate to the BigQuery section in GCP, create a new dataset, and then define a table schema that matches the structure of your CSV or JSON files. Specify appropriate data types for each column to ensure compatibility.

Use the BigQuery web interface or the `bq` command-line tool to load data from your GCS bucket into BigQuery. In the web interface, use the "Create Table" option, select "Google Cloud Storage" as the source, and specify the file format. If using the `bq` tool, a command might look like `bq load --source_format=CSV dataset_name.table_name gs://your-bucket-name/file.csv`.

After loading the data, it’s crucial to verify that the data in BigQuery matches the original data from Intercom. Run queries to check the row counts and sample the data to ensure it has been imported correctly and completely. Address any discrepancies by reviewing the data preparation and loading steps.

By following these steps, you can transfer data from Intercom to BigQuery manually without the need for third-party connectors or integrations.