How to load data from Google Sheets to Snowflake

In the left sidebar, find the "Connections" section and click on "Catalog". This will open the catalog of all available sources and destinations.

In the catalog, use the search bar or scroll down to the Sources section. Find and click on the Google Sheets card.

On the "Add Google Sheets connection" page, you are offered two authorization methods.

• Method 1: Authenticate with Google Account .
  This is a quick authorization via OAuth, suitable for individual users and small teams. If you choose this, click "Log in to your Google Sheets account" and follow the standard Google auth flow.

• Method 2: GCP Service Account.
  This is the recommended method for enterprise use, as it provides secure, centralized access without using personal accounts.

If you select GCP Service Account, follow the steps below to generate and upload the required JSON key.

In the Google Cloud Console, navigate to the main menu (☰), then select "APIs & Services" → "Library".

In the API Library search bar, type "Google Sheets API" and select it from the results. On the API page, click the "Enable" button if it's not already enabled.

In the main GCP navigation menu (☰), go to "IAM & Admin" → "Service Accounts".

On the "Service Accounts" page, click the "+ Create Service Account" button at the top.

You will now see the "Create service account" form. You only need to fill in the first section.

• Service account name.
  Enter a descriptive name for your service.
  Example: renta-sheets-reader

• Service account ID.
  This will be automatically generated based on the name you entered. You can leave this as the default.

• Service account description.
  Recommended: add a description of what this account will do.
  Example: Reads data from Google Sheets for Renta

You will be back on the "Service Accounts" list. Find the account you just created (e.g., renta-sheets-reader@...) and click on its email address to open its details page.

On the account's details page, click the "Keys" tab. Then, click "Add Key" and select "Create new key" from the dropdown menu.

A pop-up will appear. Ensure the Key type is set to "JSON" (the default) and click "Create". Your browser will automatically download the JSON key file. Save it in a secure location.

Copy the email address of your new Service Account from the GCP console. Open any Google Sheets document you want to sync, click the "Share" button, and paste the email. Assign the "Viewer" role and click "Share".

Return to the Renta interface. Click "Upload a Service Account JSON file" and select the key you just downloaded. After successful validation, you will be redirected to the connection configuration screen.

After authorizing (via either OAuth or Service Account), Renta will ask you to configure the connection.

Fill in the two required fields:

1. Source name.
   Specify a unique, friendly name for this connection (e.g., McDonald's Marketing KPI 2025).
   This name is only used in the Renta interface.

2. Google Spreadsheet ID.
   In this field, paste the full URL of the Google Sheet document.
   Renta will automatically parse the URL and extract the ID.

Go back to the "Connections" → "Catalog" section in the left sidebar.

In the catalog, scroll to the Destinations section or use the search. Find and click on the Snowflake card.

Fill in the following fields:

1. Destination name.
   A friendly name for the connection in the Renta UI.
   Example: Snowflake Production DWH.

2. Server hostname.
   Example: https://y12345.eu-central-1.snowflakecomputing.com

3. Warehouse.
   The name of the Snowflake Warehouse to use for loading operations.
   Example: RENTA_WAREHOUSE.

4. Database name.
   Example: RENTA_DATABASE.

5. Database schema.
   Example: RENTA_DATABASE.

6. User.
   Example: RENTA_USER .

7. Password.
   Example: MY_PASSWORD .

In the left sidebar, click on "New pipeline". This will open the pipeline creation wizard.

On the first screen, you'll see a list of your configured sources. Select the Google Sheets connection you created earlier and click "Next step".

Choose the connection that was created in the first step.

On the next screen, select your configured Snowflake connection and click "Next step".

Choose the destination that was created in the second step.

On the final screen, we'll configure the pipeline settings.

Select the Worksheet

In the Worksheets dropdown menu, select the specific sheet (tab) from your Google Sheets document that you want to sync. The current version works with one sheet at a time—to sync multiple sheets, simply create a separate pipeline for each.

Specify the Header Row

In the Header row number field, specify which row contains your column names. The default is "Use 1st row as table headers," meaning Renta will interpret the first row as column headers and start reading data from the second row.

Change this value if:

• You have metadata or descriptive text in rows above your headers.

• Your headers are not in the first row.

Select Worksheet columns

The Worksheet columns field allows you to select only specific columns to sync instead of loading all of them. Leave it empty to sync all columns.

Use this option to:

• Exclude helper or utility columns

• Filter out sensitive data (PII)

• Optimize data transfer volume

In the Integration name field, provide a clear, descriptive name to identify the pipeline in the UI.
The default is "Google Sheets," but we recommend changing it.

Example: Marketing Budget Tracker.

In the Table name field, specify the name of the table that will be created in Snowflake.
Renta auto-generates a name like google_sheets_[timestamp], but it's best practice to set a descriptive name.

Naming rules:

• Use snake_case: sales_daily, marketing_budget_tracker_2025

• Use only letters, numbers, and underscores.

• Do not start with a number.

• Avoid SQL reserved words.

Choose one of the four schedule types:

If you selected a Manual schedule, or if you don't want to wait for the next scheduled run, click the "Run Now" button on the pipeline's page in Renta.

The pipeline's page will display the status of the current run: in progress, completed, or error.

Detailed logs show each step of the execution:

• run_created — Pipeline initiated

• run_started — Data extraction began

• run_rows_extracted — Data extracted (with row count)

• run_data_loaded — Data loaded into Snowflake

• run_ended — Run finished successfully

If a run fails, the logs will provide a detailed error message and recommended actions.

Open your Snowflake web interface or DB client and run a query:

-- Check if the table exists
SHOW TABLES LIKE 'your_table_name' IN SCHEMA your_database.your_schema;

-- Preview the first 10 rows
SELECT *
FROM your_database.your_schema.your_table_name
LIMIT 10;

-- Check the row count
SELECT COUNT(*)
FROM your_database.your_schema.your_table_name;

Verify that:

• The table was created with the correct name.

• The row count matches what you expect from Google Sheets.

• The column names match your headers from the Google Sheet.

• The data has been loaded correctly without distortion.