BigQuery is a powerful data warehouse by Google Cloud that handles large-scale data analytics. Connecting BigQuery to Google Sheets using Superjoin.ai allows you to easily import data for analysis and reporting without requiring advanced technical skills.

Pulling data from BigQuery into Google Sheets centralizes your information for easy access and management. It enables the creation of custom reports and dashboards, while Google Sheets’ collaborative features support real-time data sharing and group analysis. Additionally, Google Sheets' collaborative features enable real-time sharing, facilitating group analysis and decision-making.

This blog will compare different methods to connect BigQuery and Google Sheets, highlighting why Superjoin is often the best choice for many users.

Best Ways to Connect BigQuery to Google Sheets

Method 1: Using Superjoin

Superjoin provides the fastest and easiest way to connect BigQuery to Google Sheets without any technical know-how or complex setup processes. Here’s how it works:

Step 1: Click Extensions from the Google Sheets menu. Select Add-ons and choose to Get Add-ons. This will bring you to the Google Workspace Marketplace.

Step 2: Look for Superjoin in the Google Marketplace pop-up window and install the app by following the prompts.

Step 3: Navigate back to the Extensions menu tab and launch Superjoin from there. You should see Superjoin running as a Google Sheets side panel on the right side of your screen. 

Step 4: From Sources, select BigQuery from the list.

Step 5: After selecting BigQuery, enter your Project ID (GCP Project ID associated with the BigQuery dataset). After entering go ahead and click on the "Connect" button.

Step 6: Choose between three query methods through which you would like to import.

Step 7: Enter your SQL query and click Run query and then you can preview your data.

Step 8: Once you have previewed the data select Import and wait for a few seconds. This action pulls all your data from BigQuery to Google Sheets.

Step 9: Superjoin lets you refresh your imported data instantly with one click or set it to auto-refresh on a pre-set schedule. This way, you won't need to manually update your BigQuery data in Google Sheets to reflect changes from the source.

Voila, you've successfully imported your BigQuery data to Google Sheets using Superjoin!

It is particularly suitable for users looking for a BigQuery to Google Sheets free tool, as Superjoin offers a free tier.

Method 2: Using Google’s Connected Sheets

Google Sheets’ Connected Sheets feature allows you to schedule automatic transfers of data directly from BigQuery into Google Sheets. This method is useful for importing large datasets and staying updated with the latest company data.

How It Works:

1. Navigate in Google Sheets: In the navigation menu of Google Sheets, select Data > Data Connector > Connect to BigQuery.

   
   

2. Select BigQuery Data: Choose your desired BigQuery project, dataset, and table or view.

   
   

3. Data Import: Your selected dataset will appear in the Google Sheets file, with Google automatically fetching the data into a new tab.

   
   

Limitations: While this method effectively brings BigQuery data into Sheets, it is limited to BigQuery and requires manually navigating through multiple steps without previewing your data and this is limited to 25,000 rows.

Method 3: Using Google Apps Script

For those with coding knowledge, Google Apps Script is a powerful scripting language based on JavaScript that allows you to extend the functionality of Google Sheets and automate tasks.

Here’s how you can use it to connect BigQuery to Google Sheets:

Step 1: Open a new or existing Google Sheets spreadsheet.

Step 2: Click on “Extensions” > “Apps Script” to open the Google Apps Script editor.

Step 3: Use the BigQuery service in Google Apps Script to connect to your BigQuery project.

• Write a function to authenticate with BigQuery, execute a SQL query, and retrieve the data.

• Parse the retrieved data and insert it into the desired cells in Google Sheets.

Example snippet to connect to BigQuery:

function getBigQueryData() {
  var projectId = 'YOUR_PROJECT_ID';
  var request = {
    query: 'SELECT * FROM `YOUR_DATASET.YOUR_TABLE` LIMIT 1000;',
    useLegacySql: false
  };
  var queryResults = BigQuery.Jobs.query(request, projectId);
  var rows = queryResults.rows;
  var sheet = SpreadsheetApp.getActiveSpreadsheet().getActiveSheet();
  
  // Loop through the results and insert into Google Sheets
  for (var i = 0; i < rows.length; i++) {
    sheet.appendRow(rows[i].f.map(function(field) {
      return field.v;
    }));
  }
}

Step 4: Modify the script with your Project ID and run the script to pull data from your BigQuery into Google Sheets.

Limitations of Using Google Apps Script:

• Requires technical expertise, making it challenging for non-developers.

• Time-consuming setup and ongoing maintenance, particularly with debugging and updates.
  
  

Why Choose Superjoin?

In comparison to other methods, Superjoin stands out for several reasons:

• Easy to Use: Superjoin’s intuitive interface makes connecting BigQuery to Google Sheets simple, even for non-technical users.

• Saves Time: Streamlines data imports without the need for complex configurations or manual effort.

• Automated Updates: Keeps your Google Sheets data current with automated imports.

• Versatile: Supports multiple data sources, including MongoDB, beyond what alternatives like Connected Sheets offer.

For users looking for a simple, efficient, and integrated solution to connect BigQuery with Google Sheets, Superjoin is a superior choice. It minimizes the need for technical expertise and automates the data import process, allowing you to focus on deriving insights rather than managing data imports.