Google Cloud & Analytics Integration

The Google Cloud integration suite allows you to automate data analysis, database management, and query execution within your Google Cloud projects.

How to get credentials

These nodes typically require a Service Account.

1. Go to the Google Cloud Console.
2. Select your project and ensure the relevant APIs are enabled (e.g., Google Analytics API, BigQuery API, Cloud Firestore API).
3. Navigate to IAM & Admin → Service Accounts.
4. Create a new service account and grant it the appropriate roles (e.g., BigQuery Data Editor, Cloud Datastore User for Firestore, or Viewer for Analytics).
5. Generate a new JSON key for the service account and download it.
6. In Nodes2Cloud, create a new Google credential using the Service Account method and paste the JSON contents.

(Note: For Google Analytics 4, you must also add the service account's email address as a user with "Read & Analyze" permissions in your GA4 Property Access Management settings).

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1. Google Analytics (GA4)

What the node does

Retrieves reporting data and metrics from Google Analytics 4 properties.

Options / Fields

• Credential: Your Google Service Account credential.
• Property ID: The numeric ID of your GA4 property (found in GA4 Admin → Property Settings).
• Start Date / End Date: The date range for the report (e.g., today, yesterday, 30daysAgo, or YYYY-MM-DD).
• Dimensions: The criteria by which to group data (e.g., city, browser, date).
• Metrics: The quantitative measurements to retrieve (e.g., activeUsers, screenPageViews, sessions).

How to set it up

1. Enter your Property ID.
2. Select the Dates, Dimensions, and Metrics.
3. The node will output an array of rows containing the requested analytics data.

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2. Google BigQuery

What the node does

Executes SQL queries against your BigQuery datasets or inserts new rows directly into tables.

Sub-Nodes / Actions

• BigQuery: Execute Query: Runs a standard SQL query and returns the results.
• BigQuery: Insert Rows: Streams data directly into a BigQuery table.

Common Fields

• Project ID: Your Google Cloud Project ID.
• Dataset ID: The ID of your BigQuery dataset.
• Table ID: The ID of the specific table.
• SQL Query: (For querying) The standard SQL query to execute.
• Data (JSON): (For inserting) The JSON array of rows to insert.

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3. Google Firestore

What the node does

Read, write, update, and delete documents within a Cloud Firestore database.

Sub-Nodes / Actions

• Firestore: Get Document: Retrieves a single document by its path.
• Firestore: Query Collection: Searches for documents in a collection matching specific filters.
• Firestore: Create/Update Document: Upserts data into a specific document path.
• Firestore: Delete Document: Removes a document.

Common Fields

• Project ID: Your Google Cloud Project ID.
• Collection / Document Path: The slash-separated path to the resource (e.g., users/user123 or just users).
• Data (JSON): The document payload to create or update.

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Common Troubleshooting

• Permission Denied (403): Double-check the IAM Roles assigned to your service account in the Google Cloud Console. BigQuery requires BigQuery Data Editor and BigQuery Job User. Firestore requires Cloud Datastore User.
• GA4 Property ID vs Account ID: Make sure you are using the Property ID (usually a 9-digit number), not the Account ID or the old Universal Analytics UA- tracking ID.
• Firestore Path Formatting: Firestore paths must alternate between collections and documents. A path like users/user123 points to a document. A path like users points to a collection. Nodes requiring a document (like Get or Update) will fail if given a collection path.