Instrucciones y requisitos de configuración del lab
Protege tu cuenta y tu progreso. Usa siempre una ventana de navegador privada y las credenciales del lab para ejecutarlo.

Pulling BigQuery Data into Google Sheets using BigQuery Connected Sheets

Lab 30 minutos universal_currency_alt 5 créditos show_chart Introductorio
info Es posible que este lab incorpore herramientas de IA para facilitar tu aprendizaje.
Este contenido aún no está optimizado para dispositivos móviles.
Para obtener la mejor experiencia, visítanos en una computadora de escritorio con un vínculo que te enviaremos por correo electrónico.

Overview

In this scenario, you are a data analyst with strong experience in Google Sheets but are new to BigQuery. You are employed with a solar energy company who is interested in identifying U.S. counties with the highest number of homeowners who can benefit from a new grant. The new United States (U.S.) federal grant is available to homeowners with homes built before 1960 and annual incomes below $60,000 USD. You know that the necessary data to identify these homeowners is in your company's BigQuery data warehouse and would like to analyze the BigQuery data in Google Sheets.

Through the BigQuery data connector in Google Sheets, Connected Sheets provides you with the ability to access, analyze, visualize, and share BigQuery data without the need for any SQL.

In this lab, you learn how to get started with BigQuery data in Google Sheets by using the BigQuery data connector to pull data from BigQuery tables (in a Google Cloud project) into Google Sheets.

Objectives

In this lab, you will learn how to perform the following tasks:

  • Open the BigQuery data connector in Google Sheets.
  • Connect to a BigQuery table and pull the data into a Google Sheet.

Setup

For each lab, you get a new Google Cloud project and set of resources for a fixed time at no cost.

  1. Sign in to Google Skills using an incognito window.

  2. Note the lab's access time (for example, 1:15:00), and make sure you can finish within that time.
    There is no pause feature. You can restart if needed, but you have to start at the beginning.

  3. When ready, click Start lab.

  4. Note your lab credentials (Username and Password). You will use them to sign in to the Google Cloud Console.

  5. Click Open Google Console.

  6. Click Use another account and copy/paste credentials for this lab into the prompts.
    If you use other credentials, you'll receive errors or incur charges.

  7. Accept the terms and skip the recovery resource page.

Task 1. Open a new Google Sheet

In this first task, you log into Google Workspace in this lab environment using the provided credentials and then open a new Google Sheet.

  1. To open Sheets, right-click this provided link for Open Google Sheets, and select the option to open the link in a new incognito window.

  2. To sign into Google Workspace, use the credentials (username and password) provided on the current lab page.

Be sure to:

  • Accept the terms and conditions.
  • Do not add recovery options or two-factor authentication (because this is a temporary account).
  • Exit the Welcome to Google Sheets window.
Note: Be sure to log into Google Workspace using the provided lab credentials. If you use your personal Google Cloud account, you may incur charges when connecting to BigQuery and other Google Cloud resources.
  1. On the Sheets main page, click the + (plus sign) for Blank spreadsheet.

click_plus_blank_spreadsheet.png

Task 2. Pull data using the BigQuery data connector

In BigQuery, a table ID contains all of the information needed to locate the table (including the names of the Google Cloud Project, the BigQuery dataset, and the table) and is structured as follows:

  • project_name.dataset_name.table_name

In this task, you use the BigQuery data connector to connect and pull the data from the following table in your lab-provided Google Cloud project into Google Sheets:

  • .public_sector.censustract_2018_5yr
  1. In the menu bar of your Google Sheet, select Data > Data connectors > Connect to BigQuery.

open_bq_dataconnector.svg

  1. For Choose a cloud project, search for the project name.

  2. For Choose a dataset, select public_sector.

  3. For Choose a table or view, select censustract_2018_5yr.

  4. Click Connect.

success_data_connected.svg

After a successful data connection, the data will populate the Google Sheet and resemble the following table structure with 74,000 records.

geo_id do_date total_pop households more columns...
72021031033 2014-01-01 4234 1536 ...
72137122100 2014-01-01 2483 834 ...
72025200700 2014-01-01 3832 1445 ...
72021031021 2014-01-01 3555 1376 ...
72135510601 2014-01-01 5915 1550 ...

Click Check my progress to verify the objective. Pull data from censustract_2018_5y using the BigQuery data connector

Challenge

Test your new skills by pulling in another BigQuery dataset into your Google Sheet.

For this challenge, repeat the lab tasks as needed to pull data from the following BigQuery table ID:

  • .public_sector.censustract_2018_5yr_top10000_housingunits

After a successful data connection, the data will populate the Google Sheet and have the same table structure as censustract_2018_5yr but only contain 10,000 records.

Click Check my progress to verify the objective. Pull data from censustract_2018_5yr_top10000_housingunits using the BigQuery data connector

Congratulations!

You have successfully used the BigQuery data connector to pull data from a BigQuery table into your Google Sheet!

Last Tested Date: November 04, 2022

Last Updated Date: November 04, 2022

End your lab

When you have completed your lab, click End Lab. Google Skills removes the resources you’ve used and cleans the account for you.

You will be given an opportunity to rate the lab experience. Select the applicable number of stars, type a comment, and then click Submit.

The number of stars indicates the following:

  • 1 star = Very dissatisfied
  • 2 stars = Dissatisfied
  • 3 stars = Neutral
  • 4 stars = Satisfied
  • 5 stars = Very satisfied

You can close the dialog box if you don't want to provide feedback.

For feedback, suggestions, or corrections, please use the Support tab.

Copyright 2026 Google LLC All rights reserved. Google and the Google logo are trademarks of Google LLC. All other company and product names may be trademarks of the respective companies with which they are associated.

Antes de comenzar

  1. Los labs crean un proyecto de Google Cloud y recursos por un tiempo determinado
  2. .
  3. Los labs tienen un límite de tiempo y no tienen la función de pausa. Si finalizas el lab, deberás reiniciarlo desde el principio.
  4. En la parte superior izquierda de la pantalla, haz clic en Comenzar lab para empezar

Usa la navegación privada

  1. Copia el nombre de usuario y la contraseña proporcionados para el lab
  2. Haz clic en Abrir la consola en modo privado

Accede a la consola

  1. Accede con tus credenciales del lab. Si usas otras credenciales, se generarán errores o se incurrirá en cargos.
  2. Acepta las condiciones y omite la página de recursos de recuperación
  3. No hagas clic en Finalizar lab, a menos que lo hayas terminado o quieras reiniciarlo, ya que se borrará tu trabajo y se quitará el proyecto

Este contenido no está disponible en este momento

Te enviaremos una notificación por correo electrónico cuando esté disponible

¡Genial!

Nos comunicaremos contigo por correo electrónico si está disponible

Un lab a la vez

Confirma para finalizar todos los labs existentes y comenzar este

Usa la navegación privada para ejecutar el lab

Usar una ventana de incógnito o de navegación privada es la mejor forma de ejecutar este lab. Así evitarás cualquier conflicto entre tu cuenta personal y la cuenta de estudiante, lo que podría generar cargos adicionales en tu cuenta personal.