Google Sheets

Follow our setup guide to connect Google Sheet to QUANTI:

Prerequisites

To connect a Google Sheet to QUANTI, you need to:

• Access a Google Drive account

• Have edit access to the Google Sheet you want to use

• Create a named range in your Google Sheet (see instructions below)

Named Range

Open your Google Sheet, then go to Data > Named ranges and create a named range.

Steps to create a named range:

1

1. Select the range you want to sync, including the header row

2

1. Go to Data > Named ranges

3

1. Give it a name of your choice

4

1. Ensure the selected range includes:

• The header row with a name for each column

• All data rows you want to sync

5

1. Click Done

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Setup Instructions

1

Authorize Google Connection

• Click on Connect to Google Sheets

• You will be redirected to Google's authorization page

• Log in with your Google account credentials

• Review and accept the requested permissions

• Click Allow to grant QUANTI access to your Google Sheets

Click Next

2

Connector Information

• Connector Name: Name your connector. It must be unique.

• Dataset ID: Define the ID of the dataset. It must not exist yet, as it will be created and data will be sent there.

Click Next

3

Select Google Sheet and Range

• Browse: Use the Google Picker to select your Google Sheet from your Google Drive.

• Named Range: Select the named range you want to sync

  • The named range must be created beforehand in your Google Sheet

  • The first row of the range will be used as column headers

Click Next

4

Sync Behavior

Choose the data insertion method that fits your use case:

• Table Type: Select your table type:

  • Fact table: A table containing metrics and date-based data (e.g., sales, events, transactions)

  • Dimension table: A table composed exclusively of descriptive attributes (e.g., products, customers, categories)

• Sync Method: Choose your insertion method: Learn more.

  • INSERT: Add new rows without checking for duplicates (recommended for time-series data)

  • REPLACE: Delete rows within the table scope and reload new rows

  • UPSERT: Update existing rows or insert new ones based on primary key (requires unique identifier) - No rows deleted

If you have difficulties determining the most accurate configuration for your case, discover our guide.

Click Next

5

Mapping Configuration

Table Configuration

• Destination table name: Define your BigQuery table name (lowercase, underscores only)

Field Mapping

For each column detected in your sample file:

• Destination field name: Define the column name in BigQuery (lowercase, underscores recommended)

• Data type: Choose the appropriate type:

  • STRING - Text values, alphanumeric data

  • INTEGER - Whole numbers (e.g., 42, -10, 0)

  • FLOAT - Decimal numbers (e.g., 3.14, -0.5)

  • BOOLEAN - True/False values

  • DATE - Date only (format: YYYY-MM-DD)

  • TIMESTAMP - Date and time with timezone

  • DATETIME - Date and time without timezone

Date Column (mandatory for Fact tables)

• Select the date field for table partitioning

• This field is mandatory for all methods when Fact table was selected in Step 2

• Used for optimizing query performance and data organization

• Must be a valid date/timestamp field in your data

Historize Changes

• Required if UPSERT was selected in Step 2 (Sync Behavior)

• Optional for INSERT and REPLACE methods

• Selected fields: Values are historized (previous versions are kept)

• Deselected fields: Values are updated without keeping history

Click Next

6

Finish Setup

• Save your sync settings

• You can now active the auto-sync or launch a sync now.