Installation & Initial Setup
How to connect Odoo with Google BigQuery using the Niyu Labs Connector
The official installation and setup guide for the Niyu Labs Google BigQuery Connector. Unlock your Odoo data's full potential by integrating it with Google's powerful analytics platform.
1. Requirements
Before starting, please ensure you have the following:
Odoo Instance:
Versions Supported: 12, 13, 14, 15, 16, 17,18
Edition: Enterprise or Community
Google Cloud Platform Account: An active account with the BigQuery API enabled.
Permissions:
Odoo: Administrator access to install modules and configure settings.
Google Cloud: Permissions to create projects, datasets, service accounts, and assign IAM roles.
Python Libraries: This module depends on google-cloud-bigquery, pandas, and pyarrow.
For Odoo.sh: Add these library names to your repository's requirements.txt file.
For On-Premise Servers: Install them manually into your Odoo Python environment (pip3 install google-cloud-bigquery pandas pyarrow) and restart your Odoo server.
2. Installation
Download the Module: Obtain the Niyu Labs BigQuery Connector from the Odoo Apps Store: https://apps.odoo.com/apps/modules/18.0/odoo-bigquery
Update Apps List: In your Odoo instance, enable Developer Mode, then navigate to Apps and click Update Apps List.
Install the Module: In the Apps menu, search for Niyu Labs Pro BigQuery Connector and click Install.
3. Configuration: Part A - Google Cloud Setup
First, we need to create the necessary credentials in your Google Cloud account.
3.1. Get Your Project ID and Dataset ID
Log in to the Google Cloud Console.
Navigate to the BigQuery section.
Select an existing project or Create a new project.
Important: The Project ID must be globally unique. Note it down. [Screenshot of Google Cloud Console showing the Project ID]
Within your project, create a new Dataset. This is where your Odoo tables will be stored.
Important: The Dataset ID will be used in the Odoo configuration. Note it down. [Screenshot of the 'Create dataset' dialog in BigQuery]
3.2. Create a Service Account & Credentials JSON
A service account allows Odoo to securely authenticate with your Google Cloud project.
In the Google Cloud Console, navigate to IAM & Admin → Service Accounts.
Click CREATE SERVICE ACCOUNT. Give it a name (e.g., odoo-connector-niyu-labs).
Grant Permissions: Assign the following roles to the service account to allow it to manage data and run jobs. For optimal security, use these specific roles:
BigQuery Data Editor
BigQuery Job User
(Alternatively, for simplicity, you can assign the BigQuery Admin role). [Screenshot showing the assignment of IAM roles]
Generate a JSON Key:
After creating the service account, click on it from the list.
Go to the KEYS tab.
Click ADD KEY → Create new key.
Choose JSON as the key type and click CREATE.
A JSON file will be downloaded to your computer. Keep this file secure, as it contains your credentials. [Screenshot of the 'Keys' tab with the 'Add Key' button highlighted]
4. Configuration: Part B - Odoo Setup
Now, let's connect Odoo to BigQuery using the credentials you just created.
Enter Credentials in Odoo:
In Odoo, navigate to Settings → General Settings and scroll down to the Niyu Labs BigQuery Connector section.
Enter the BigQuery Project ID and BigQuery Dataset ID you noted down earlier.
Open the downloaded JSON key file in a text editor, copy its entire contents, and paste it into the BigQuery Credentials JSON field.
Click SAVE.
Test the Connection:
Click the Save button after adding the credentials.
A success notification confirms that your credentials are correct and Odoo can communicate with your BigQuery project.
5. Creating Your First Smart Export
The Niyu Labs connector uses Export Configurations to give you granular control over your data syncs. This is where you define exactly what data to send and how often to send it.
Navigate to Settings → Technica → Database Structure → BigQuery Export Configurations and click Create.
Step 1: Basic Setup
Name: Give your configuration a descriptive name (e.g., "Confirmed Sales Orders").
Odoo Model: Select the Odoo model you want to export (e.g., sale.order).
Step 2: Column Filtering (Optional)
Go to the Fields to Export tab.
Click Add a line to choose the specific fields you want in your BigQuery table. If you leave this empty, all fields will be exported.
Why? This is perfect for excluding sensitive data and keeping your BigQuery tables lean and optimized. [Screenshot of the 'Fields to Export' tab with a few fields selected]
Step 3: Record Filtering with Domain (Optional)
Use the Domain Filter field to specify exactly which records to export using Odoo's domain syntax.
Example: To export only confirmed sales orders, use: [('state', 'in', ['sale', 'done'])]
Step 4: The 'One-Click' Automated Sync
This is where the magic happens. No need to manually create complex cron jobs!
Check the box Enable Incremental Sync.
Sync Field: Select a date field to track changes. write_date is recommended to capture both new and updated records.
Sync Frequency: Choose how often you want the sync to run (e.g., Hourly, Daily, Weekly). The connector automatically creates and manages the scheduled action for you. And boom, your automation is live!
6. Execution and Verification
Run the First Export:
After saving your configuration, click the Run Export Now button to perform the initial full data transfer. [Screenshot of the 'Run Export Now' button on the configuration form]
Check BigQuery:
Log back into your Google Cloud Console and go to your BigQuery dataset.
Refresh the explorer panel. You will see a new table named after your Odoo model (e.g., sale_order).
Click on the table and use the Preview tab to confirm that your data has arrived correctly, respecting your column and domain filters. [Screenshot of BigQuery showing the newly created table and its data preview]
Congratulations! Your smart export is now configured. The Niyu Labs connector will now automatically keep your BigQuery dataset up-to-date based on the schedule you defined, syncing only the changes efficiently and cost-effectively.
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