How to Use BigQuery in Google Sheets?

Google BigQuery is a cloud-based data warehouse designed for analyzing large amounts of data quickly and efficiently. Many beginners wonder, what is BigQuery used for?Simply put, it is used to store, manage, and analyze massive datasets using standard SQL — without needing your own servers.

When you connect BigQuery with Google Sheets, you can easily run SQL queries, view live data, and create reports directly in Sheets. This integration saves time and eliminates the need for exporting or importing data files manually.

In this step-by-step guide, you’ll learn:

1. How to create a database (dataset) in BigQuery

2. How to connect BigQuery to Google Sheets

3. How to run SQL queries in Google Sheets

4. How to schedule automatic data refresh

5. Best practices for beginners

This blog is written for complete beginners who want to analyze data professionally using Google tools.

1. What You Need Before You Start

Before learning how to connect BigQuery to Google Sheets, make sure you have:

• A Google account (Gmail or Google Workspace)

• Access to Google Cloud Console

  

  How to create a database (dataset) in BigQuery

• BigQuery enabled in your Google Cloud project

• Google Sheets (visit https://sheets.google.com)

2. What Is BigQuery Used For?

BigQuery is mainly used for:

• Analyzing large-scale data across millions of rows in seconds

• Running SQL queries without managing databases or servers

• Creating reports and dashboards for business insights

• Connecting to tools like Google Sheets, Looker Studio, and Data Studio

It’s ideal for companies that deal with sales data, website analytics, or any kind of structured data that grows daily.

3. How to Create a Database (Dataset) in BigQuery

If you’re new, follow these simple steps to set up your first BigQuery dataset.

Step 1: Open Google Cloud Console

1. Visit https://console.cloud.google.com/.

2. Sign in using your Google account.

Step 2: Create a Project

1. Click on your project name (or “Select a project”) at the top.

2. Choose New Project.

3. Give it a name, such as sales-demo-project.

4. Click Create.

   

   how to create project in Google Cloud console

Step 3: Open BigQuery

1. From the left menu (☰), go to Big Data → BigQuery.

2. BigQuery will open in a new tab.

   

   How to open BigQuery in Google Cloud Console

Step 4: Create a Dataset (Your Database)

1. In the left panel, click the three dots (⋮) next to your project name.

2. Choose Create dataset.

3. Enter:

   • Dataset ID: Example: sales_data

   • Data location: Choose a region (e.g., US or asia-south1).

4. Click Create dataset.

   

   how to set up dataset in Big Query

Step 5: Add a Table

1. Open the dataset you just created.

2. Click Create table.

3. Choose Upload and select a CSV file from your computer.

4. Click Create table.

Your BigQuery database is now ready.

How to create table in Big Query?

4. How Do I Connect BigQuery to Google Sheets?

Once your dataset is ready, you can easily connect it to Google Sheets using the built-in Data Connector feature.

Step-by-Step Process:

1. Open a new or existing Google Sheet.

2. Click Data → Data connectors → Connect to BigQuery.

3. Select your Google Cloud project.

4. Pick your dataset and table.

5. Click Connect.

   

   How Do I Connect BigQuery to Google Sheets?

Your BigQuery data will appear directly in Google Sheets.You can sort, filter, and analyze it like any other sheet data — but the data remains stored securely in BigQuery.

How Do I Connect BigQuery to Google Sheets?

5. Can You SQL Query in Google Sheets?

Yes, you can run SQL queries directly inside Google Sheets. This is one of the most powerful features of the BigQuery integration.

To do this:

1. Go to Data → Data connectors → Connect to BigQuery.

2. Select your project.

3. Choose Custom query.

4. Write your SQL query. For example:

   SELECT product, SUM(sales_amount) AS total_sales FROM `project_id.sales_data.sales_table` WHERE region = 'West' GROUP BY product ORDER BY total_sales DESC;

5. Click Connect.

6. The query results will appear directly in your Google Sheet.

You can also refresh results anytime by going to Data → Data connectors → Refresh results.

6. Can Google Sheets Handle Big Data?

Normally, Google Sheets can’t handle very large datasets (it has a 10 million cell limit).However, when you connect Sheets to BigQuery using Connected Sheets, it can analyze huge datasets because the heavy processing happens in BigQuery — not in Sheets.

So yes, Google Sheets can handle big data when connected to BigQuery, since it only loads the results you query, not the entire table.

7. How to Schedule Automatic Data Refresh

If your BigQuery data changes daily or hourly, you can schedule automatic refreshes in Sheets.

1. In the Sheet, click Data → Data connectors → Schedule refresh.

2. Choose how often you want to refresh (Hourly, Daily, or Weekly).

3. Turn on email notifications for any refresh failures.

This feature keeps your reports and dashboards always updated without manual work.

8. Best Practices for Beginners

Tip	Reason
Select only the columns you need	Reduces query cost and improves performance
Avoid using SELECT *	Loads unnecessary data
Start with small datasets	Easier to learn and test
Share access carefully	Others need BigQuery access too
Monitor query cost	BigQuery charges based on data processed

9. Example Use Case

Suppose you have a table named sales_table with these columns:

• product_name

• region

• sales_amount

You can use this query inside Google Sheets:

SELECT region, SUM(sales_amount) AS total_sales
FROM `project_id.sales_data.sales_table`
GROUP BY region
ORDER BY total_sales DESC;

This will show total sales per region directly in your Google Sheet.You can then use Insert → Chart in Sheets to visualize the data.

Conclusion

BigQuery and Google Sheets together make it easy for anyone to analyze large datasets without advanced tools or programming.

• BigQuery is used to store and analyze large-scale data using SQL.

• Google Sheets provides an easy-to-use interface for reports and dashboards.

• By connecting the two, you can run SQL queries, handle big data, and automate reporting — all in one place.

Even if you’re a beginner, you can start today by:

1. Creating a BigQuery project and dataset

2. Uploading a simple CSV file

3. Connecting it to Google Sheets

4. Running your first SQL query

Once you get comfortable, you can build live dashboards that refresh automatically and share them with your team.