How to load data from Commcare to BigQuery

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

Try Airbyte Cloud Manual method (the hard way)

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Building in-house pipelines

Bespoke pipelines are:

Inconsistent and inaccurate data
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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 Commcare 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 Commcare 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 Commcare 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 Cloud Manual 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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Try Airbyte Cloud Manual method (the hard way)

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How to Sync to Manually

Step 1: Export Data from CommCare

Begin by exporting the necessary data from CommCare. Log into your CommCare HQ account, navigate to the "Data" section, and select "Export Form Data" or "Export Case Data," depending on your needs. Customize your export by selecting the specific forms or cases, and choose the data fields required. Export the data in a CSV format for easier handling in subsequent steps.

Step 2: Set Up a Google Cloud Project

Log in to your Google Cloud Platform (GCP) account and create a new project or select an existing one. Ensure that you have the necessary permissions to create BigQuery datasets and tables within this project. This setup is crucial for organizing and storing your data in BigQuery.

Step 3: Enable BigQuery API

In your Google Cloud project, navigate to the "APIs & Services" section and enable the BigQuery API. This will allow you to interact with BigQuery programmatically, which is necessary for loading data and managing your datasets and tables.

Step 4: Prepare Data for Import

Prepare the exported CSV data from CommCare for import into BigQuery. Cleanse and transform the data as needed, ensuring that it matches the schema requirements of your BigQuery table. You may need to use a tool like Google Sheets, Excel, or a script in Python or another language to adjust the data formatting and verify data integrity.

Step 5: Create a BigQuery Dataset and Table

In the Google Cloud Console, navigate to BigQuery and create a new dataset to store your data. Within this dataset, create a table with a schema that matches the structure of your CSV data. Define the appropriate data types for each column to ensure compatibility and optimal performance.

Step 6: Upload CSV File to Google Cloud Storage

Use Google Cloud Storage (GCS) to host your CSV file temporarily before importing it into BigQuery. Upload the file to a GCS bucket associated with your project. You can do this through the GCP Console or using the `gsutil` command-line tool. Ensure that the bucket permissions allow BigQuery to access the file.

Step 7: Load Data from Google Cloud Storage to BigQuery

Finally, load your data from GCS into BigQuery. In the BigQuery web UI, use the "Create Table" function, selecting "Google Cloud Storage" as the source. Provide the URI of your uploaded CSV file, and ensure the schema matches your table. Configure any necessary options, such as field separators or header rows, and start the import process. Once complete, your CommCare data will be available in BigQuery for analysis and reporting.

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