Get started with BigQuery data in Google Sheets (2024)

You can access, analyze, visualize, and share billions of rows of data from your spreadsheet with Connected Sheets, the new BigQuery data connector. You can also use Connected Sheets to:

  • Collaborate with partners, analysts, or other stakeholders in a familiar spreadsheet interface.
  • Ensure a single source of truth for data analysis without additional .csv exports.
  • Streamline your reporting and dashboard workflows.

Connected Sheets runs queries on BigQuery on your behalf either when manually requested or on a defined schedule. Results of those queries are saved in your spreadsheet for analysis and sharing.

Watch a video tutorial to learn more about working with BigQuery data in Google Sheets.

Tip: If you used the historical data connector, you can use extracts to create the same table view you see in your previous workflow. You can also set up scheduled refreshes to automatically update your data.

Important: When you accessBigQuery data inConnected Sheets, entries are recorded in Cloud Audit Logs. The logs show who accessed the data and when. Only people with proper authorization can access log records.

You can find thespreadsheet ID in the audit log. Every spreadsheet has a unique spreadsheet ID value containing letters, numbers, hyphens, or underscores. You can also find the spreadsheet ID in a Google Sheets URL.

Learn more about Cloud Audit Logs.

To restrict access to Google Cloud resources, you can use VPC Service Controls. Because VPC Service Controls does not support Sheets, you might not be able to access BigQuery data that VPC Service Controls protects. If you have the required permissions and meet the VPC Service Controls access restrictions, you can use the VPC Service Controls to allow queries issued through Connected Sheets.

Work with sample BigQuery data in Google Sheets

To understand how Connected Sheets works, you can explore connected sheet examples with public data.

  1. On your computer, open the Google Sheets template gallery.
  2. Choose one of the connected sheet Examples.

What you need

To access BigQuery data in Google Sheets, you need to meet all of the following requirements:

  • Access to the Google Cloud platform. If you're an admin, learn how to turn on GCP for your organization.
  • BigQuery access. Learn how to get BigQuery.
  • A project with billing setup in BigQuery. Learn how to set up Google Cloud billing.
    • If you don't have a project with billing setup, you can work with BigQuery data in a trial environment. Learn how to try BigQuery.
  • Learn more about the permissions and roles needed to access a BigQuery table or dataset.

Add a BigQuery project

Important: You can’t change BigQuery data from within Google Sheets.

  1. On your computer, open a spreadsheet in Google Sheets.
  2. In the menu at the top, click Data Get started with BigQuery data in Google Sheets (1)Data connectors Get started with BigQuery data in Google Sheets (2)Connect to BigQuery.
  3. Choose a project.
    • If you don’t find any projects, you need to add one.
  4. Choose a table or view.
    • You can pick from any company table you have access to or from public data sets.
  5. Click ConnectGet started with BigQuery data in Google Sheets (3)Start analyzing.

Use Connected Sheets on the Google Sheets app

Using the Google Sheets app on your mobile device, you can:

  • View Connected Sheets data.
  • View calculated column formulas, filters and sorts, and connection settings.
  • Copy and paste data from Connected Sheets.

To create, edit, or refresh data in Connected Sheets, open Google Sheets on a computer.

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Get started with BigQuery data in Google Sheets (2024)

FAQs

Get started with BigQuery data in Google Sheets? ›

Create or open a Google Sheets spreadsheet. Click Data, click Data connectors, and then click Connect to BigQuery. Note: If you do not see the Data connectors option, see Before you begin. Click Get connected.

How do I get data from Google sheet to BigQuery? ›

Create or open a Google Sheets spreadsheet. Click Data, click Data connectors, and then click Connect to BigQuery. Note: If you do not see the Data connectors option, see Before you begin. Click Get connected.

What is the limitation of BigQuery in Google Sheets? ›

Query jobs
LimitDefault
Maximum response size10 GB compressed
Maximum row size100 MB
Maximum columns in a table, query result, or view definition10,000 columns
Maximum concurrent slots for on-demand pricing2,000 slots per project 20,000 slots per organization
22 more rows

Is Google BigQuery easy to learn? ›

The BigQuery UI (User Interface) is designed to be easy to use and intuitive, making it easier for beginner users to get up and running quickly. The interface lets you view, query, manage easily, and store data in BigQuery tables.

How to create a table in BigQuery using Google Sheets? ›

  1. In the Google Cloud console, go to the BigQuery page. Go to BigQuery.
  2. In the Explorer pane, expand your project, and then select a dataset.
  3. In the Dataset info section, click add_box Create table.
  4. In the Create table panel, specify the following details:

How do I save BigQuery results to Google Sheets? ›

For Data location, choose the location of your data. Click Run. When the results are returned, click the Save results and select Google Sheets. If necessary, follow the prompts to log into your user account and click Allow to give BigQuery permission to write the data to your Google Drive MY Drive folder.

How to pull data from BigQuery? ›

Open the BigQuery page in the Google Cloud console. In the Explorer panel, expand your project and dataset, then select the table. In the details panel, click Export and select Export to Cloud Storage.

When should you not use BigQuery? ›

1. Data Size: BigQuery is designed to handle massive amounts of data, but there are limits. While it can handle petabyte-scale datasets, it may not be the best fit for small or moderate-sized datasets. The cost and performance benefits of BigQuery are most apparent when dealing with large volumes of data.

Is BigQuery faster than Snowflake? ›

For example, in the TPC-H benchmark, Snowflake outperformed BigQuery by about 10%. However, it is important to note that performance benchmarks can vary depending on the specific workload. For example, BigQuery may perform better than Snowflake for certain types of queries, such as complex analytical queries.

What are the disadvantages of BigQuery? ›

Limited integrations: While BigQuery is fully integrated with other GCP services, it may not have as many integrations with non-GCP tools and services as some other data warehousing solutions. Complexity: BigQuery can be complex to use, especially for users who are new to data warehousing or SQL.

How to handle large data in Google Sheets? ›

By splitting your large dataset into smaller, linked sheets and using functions like IMPORTRANGE and QUERY, you can effectively manage and analyze your data without hitting Google Sheets' cell limit. Consider using tools like data enrichment to enhance your dataset further.

How to analyse big data in Google Sheets? ›

Sheets: Get automatic pivot tables
  1. In your spreadsheet containing the source data, click Explore .
  2. Choose an option: Point to a Pivot table and click Insert Pivot table . Ask a question about your data under Answers. The results can include Pivot tables. To add one, point to it and click Insert Pivot table .

Can Google Sheets do data tables? ›

In Google Sheets, tables can simplify data creation and reduce the need to repeatedly format, input, and update data by automatically applying format and structure to ranges of data. Tables are well suited to track and organize information like: Project tracking.

How do I transfer data to BigQuery? ›

To upload data from a CSV to BigQuery, in the Create table window, select a data source and use the Upload option. Then select the file and file format. Next, define the destination for the data, specifying the name of the project and the dataset.

How do I pull data from a Google sheet? ›

Using Built-In Google Sheets Functions for Data Extraction
  1. Select the cell where you want the extracted data to appear.
  2. Type =QUERY( to start the function.
  3. Specify the data range you want to query, such as A1:D10 .
  4. Add a comma and enter your query criteria within double quotes, like "SELECT * WHERE B > 100" .
Sep 4, 2024

How to connect data to BigQuery? ›

  1. Go to the BigQuery page. ...
  2. In the Explorer pane, click add Add data.
  3. In the Add data dialog, click Connections to external data sources:
  4. In the External data source dialog, enter the following information: ...
  5. Click Create connection.
  6. Click Go to connection.

How do I get external data from Google Sheets? ›

Use import data Google Sheets functions to import external data into your spreadsheet quickly. For example, the Google Sheets IMPORTDATA function =IMPORTDATA(URL) allows you to easily pull a CSV and Tab-Separated Values (TSV) file into Google Sheets using the URL where the file is located.

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