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Lab setup instructions and requirements
Protect your account and progress. Always use a private browser window and lab credentials to run this lab.

Secure BigLake Data: Challenge Lab

Lab 10 minutes universal_currency_alt 1 Credit show_chart Introductory
info This lab may incorporate AI tools to support your learning.
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ARC129

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Overview

In a challenge lab you’re given a scenario and a set of tasks. Instead of following step-by-step instructions, you will use the skills learned from the labs in the course to figure out how to complete the tasks on your own! An automated scoring system (shown on this page) will provide feedback on whether you have completed your tasks correctly.

When you take a challenge lab, you will not be taught new Google Cloud concepts. You are expected to extend your learned skills, like changing default values and reading and researching error messages to fix your own mistakes.

To score 100% you must successfully complete all tasks within the time period!

Setup

Before you click the Start Lab button

Read these instructions. Labs are timed and you cannot pause them. The timer, which starts when you click Start Lab, shows how long Google Cloud resources are made available to you.

This hands-on lab lets you do the lab activities in a real cloud environment, not in a simulation or demo environment. It does so by giving you new, temporary credentials you use to sign in and access Google Cloud for the duration of the lab.

To complete this lab, you need:

  • Access to a standard internet browser (Chrome browser recommended).
Note: Use an Incognito (recommended) or private browser window to run this lab. This prevents conflicts between your personal account and the student account, which may cause extra charges incurred to your personal account.
  • Time to complete the lab—remember, once you start, you cannot pause a lab.
Note: Use only the student account for this lab. If you use a different Google Cloud account, you may incur charges to that account.

Challenge scenario

Your team has been asked to create a new BigLake table. Content comes from Cloud Storage and contains sensitive information so it’s important to limit access.

Your challenge

As a junior engineer, you’re asked to help with the initial work on the project by completing the following tasks:

  • Create a BigLake table from an existing file on Cloud Storage.
  • Create, apply, and verify aspects to restrict access to columns containing sensitive data.
  • Remove direct IAM permissions to Cloud Storage for other users (after aspects have been applied to protect the data).
Hint:
  • Ensure that any needed APIs (such as the BigQuery Connection API) are successfully enabled and that necessary service accounts have the appropriate permissions.
  • Create all resources in the multiple regions in the United States, unless otherwise directed.

Each task is described in detail below, good luck!

Task 1. Create a BigLake table using a Cloud Resource connection

  1. Create a BigQuery dataset named online_shop that is multi-region in the United States.

  2. Create a Cloud Resource connection named user_data_connection (multi-region in the United States) and use it to create a BigLake table named user_online_sessions in the online_shop dataset.

  • Be sure to apply the appropriate service account permissions to read Cloud Storage files in your project.
  • When creating the table, load data from the following Cloud Storage file using schema auto-detection:
    • gs://-bucket/user-online-sessions.csv

Click Check my progress to verify the objective. Create a BigLake table using a Cloud Resource connection

Task 2. Create, apply, and verify an aspect on columns containing sensitive data

  1. Create a multi-region aspect in the United States, named Sensitive Data Aspect with following field:
    • Boolean field named Has Sensitive Data.
  2. Apply the aspect to the following columns in the user_online_sessions table:
    • zip
    • latitude
    • ip_address
    • longitude

Click Check my progress to verify the objective. Apply and verify the aspect to columns containing sensitive data

Task 3. Remove IAM permissions to Cloud Storage for other users

  • Follow Google best practices after migrating data to BigLake by removing IAM permissions for user 2 () to Cloud Storage.
    • Leave the IAM role for project viewer.
    • Remove only the IAM role for Cloud Storage.

Click Check my progress to verify the objective. Remove IAM permissions to Cloud Storage for other users

Congratulations!

Secure BigLake Data badge

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...helps you make the most of Google Cloud technologies. Our classes include technical skills and best practices to help you get up to speed quickly and continue your learning journey. We offer fundamental to advanced level training, with on-demand, live, and virtual options to suit your busy schedule. Certifications help you validate and prove your skill and expertise in Google Cloud technologies.

Manual Last Updated February 17, 2026

Lab Last Tested November 06, 2025

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.

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Before you begin

  1. Labs create a Google Cloud project and resources for a fixed time
  2. Labs have a time limit and no pause feature. If you end the lab, you'll have to restart from the beginning.
  3. On the top left of your screen, click Start lab to begin

Use private browsing

  1. Copy the provided Username and Password for the lab
  2. Click Open console in private mode

Sign in to the Console

  1. Sign in using your lab credentials. Using other credentials might cause errors or incur charges.
  2. Accept the terms, and skip the recovery resource page
  3. Don't click End lab unless you've finished the lab or want to restart it, as it will clear your work and remove the project

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Use private browsing to run the lab

Using an Incognito or private browser window is the best way to run this lab. This prevents any conflicts between your personal account and the Student account, which may cause extra charges incurred to your personal account.