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Google Sheets as a Source

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Google Sheets is a cloud-based spreadsheet software developed by Google. It provides a platform for creating, editing, and collaborating on spreadsheets in real-time, offering features for data analysis, visualization, and organization, and it can be accessed through a web browser or mobile app.

Authentication Methods

Google Sheets as a Source supports more than one way to connect. Pick one when you create the authorizer in Dataddo:

  • Google Sheets - sign in with Google Sheets as a Source and approve access (recommended).
  • Google Sheets Custom - use your own app credentials (for advanced setups).
  • Google Platform Service Account - connect with a service account key, without interactive sign-in.

Prerequisites: API Call Limitations

Make sure your tables are formatted correctly to ensure proper Attributes selection in Dataddo.

The first row of the table should contain the names of the values in each column in the following way:

All limitations for API calls are described in Google's official documentation.

Authorize Connection to Google Sheets

You can authorize your Google account using:

OAuth 2.0

To authorize this service, use OAuth 2.0 to share specific data with Dataddo while keeping usernames, passwords, and other information private.

  1. On the Authorizers page, click on Authorize New Service and select your service.
  2. Follow the on-screen prompts to grant Dataddo the necessary permissions to access and retrieve your data.
  3. [Optional] Once your authorizer is created, click on it to change the label for easier identification.

Ensure that the account you're granting access to holds at least admin-level permissions. If necessary, assign a team member with the required permissions with the authorizer role to authenticate the service for you.

For more information, see our article on authorizers.

Service Account Authorization

In Google Cloud Console

To create service account, follow these steps:

  1. In your Google Cloud Console, select your project.
  2. Look up Google Sheets API using the search bar and enable the API.
  3. In the top-left of the screen, open the Navigation Menu, hover over IAM & Admin to select Service accounts.
  4. Click on three dots next service account and select Manage keys.
  5. Click on Add key and select Create new key.
  6. Choose JSON as key type. This will download the JSON file to your computer which you will later need to upload to Dataddo.

In Your Google Sheet

  1. First, open the downloaded JSON file in a text editor and copy the client email value.
  2. In your Google Sheet, share the file with the copied email address.
  3. Set the newly added email address as Editor.

In Dataddo

To authorize your service account, make sure you also have your JSON key.

  1. On the Security page, navigate to the Certificates tab and click on Add Certificate.
  2. Name your certificate, select Google Service Account Key as certificate type and upload the file you have obtained when creating a Service Account for authorization.
  3. On the Authorizers tab, click on Authorize New Service and select Google BigQuery (Service account).
  4. Select the newly added certificate.
  5. Click on Save.

Data Coverage

Google Sheets as a Source uses a single flexible dataset. You choose the fields to extract when you create the source; Google Sheets as a Source may also expose custom fields from your account.

The available fields depend on your account and the selected dataset.

How Data Extraction Works

None of this connector's datasets use a date range. Every run pulls all currently available data.

Metadata Columns

When you create a source, you can add these Dataddo metadata columns to the extracted data:

  • dataddo_hash - a fingerprint built from each record's key fields. It works as a natural key, so it is ideal for upserts (updating existing rows in your destination instead of creating duplicates).
  • dataddo_extraction_timestamp - the date and time the row was extracted. Use it to track how records change over time, for example to build slowly changing dimensions.

How to Create a Google Sheets Data Source

Creating a data source takes you through five steps, shown in the progress bar at the top of the wizard. Each step is explained below.

1. Pick the connector

On the Sources page, click Create Source, then select the connector from the catalog. Use the search bar or the category tabs if you do not see it right away. You can rename the source at any time using the pencil icon next to its name.

2. Choose the account

This step selects what Dataddo reads from.

  • Authorizer: Select an account you have already authorized from the drop-down. If you have none yet, choose Add new account and follow the prompts. If no authorizer is selected, Dataddo asks you to authorize before you continue.
  • What to extract from: Select the exact entity you want to pull data from. Depending on the service this may be labelled an account, property, profile, workspace, or similar, sometimes with a sub-level to choose as well.
  • Multiple accounts: To pull the same data from every entity you can access, turn on Automatically collect data from all .... This is multi-account extraction. Leave it off to choose them by hand.

3. Build the data model

Choose exactly what to extract. What you can pick depends on the connector, and the wizard may group the fields differently for each one.

  • Values: the measures you want, often called metrics, such as sessions, clicks, or revenue.
  • Breakdowns: the fields you group or split those values by, often called dimensions or attributes, such as date, country, or campaign.
  • Context metadata (when available): identifier fields that Dataddo derives from your selection, such as the account or property ID. They let you tell rows apart when you combine several sources.

Some connectors limit which fields can be queried together; the wizard flags this where it applies. Click Test on Sample Data at any point to preview the result before you continue.

4. Add metadata columns (optional)

Two optional columns help your destination handle the data.

  • Dataddo Hash (Include Row Hash): a fingerprint built from the columns you pick. It works as a natural key, so your destination can deduplicate rows and run upserts instead of creating duplicates. Turn it on, then select the columns that uniquely identify a row.
  • Dataddo Extraction Timestamp: the time each row was extracted. Use it to watermark the data, for example to build slowly changing dimensions or to track when a value last changed.

5. Set the schedule

Decide how often Dataddo runs the extraction.

  • Frequency: how often the pipeline runs, for example daily. Click Show advanced settings to also set the exact hour and minute (UTC).
  • Date range: the relative window each run extracts, for example "Yesterday". The window moves forward on every run.
  • Historical data: a new source starts from the current window. To load older data, run a full data re-sync after the source is created.
  • Allow Empty Data Extractions: when on, a run that returns no data records zero rows instead of failing. Turn it on if the source can legitimately have periods with no data.

Click Save. Your data source is ready.

When you build the data model, select the spreadsheet and the sheet you want to extract.

Troubleshooting

Data Preview Unavailable

No data preview when you click on Test Data might be caused by an issue with your source configuration. The most common causes are:

  • Date range: Try a smaller date range. You can load the rest of your data afterward using manual data load.
  • Insufficient permissions: Please make sure your authorized account has at least admin-level permissions.
  • Invalid metrics, attributes, or breakdowns: You may not have any data for the selected metrics, attributes, or breakdowns.
  • Incompatible combination of metrics, attributes, or breakdowns: Your selected combination cannot be queried together. Please refer to the service's documentation to view a full list of metrics that can be included in the same data source.

Related Articles

Now that you have successfully created a data source, see how you can connect your data to a dashboarding app or a data storage.

Sending Data to Dashboarding Apps

Sending Data to Data Storages

Other Resources