
Before you begin
- Labs create a Google Cloud project and resources for a fixed time
- Labs have a time limit and no pause feature. If you end the lab, you'll have to restart from the beginning.
- On the top left of your screen, click Start lab to begin
Create a BigLake table using a Cloud Resource connection
/ 30
Apply and verify policy tags on columns
/ 40
Remove IAM permissions to Cloud Storage
/ 30
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!
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 will be made available to you.
This hands-on lab lets you do the lab activities yourself in a real cloud environment, not in a simulation or demo environment. It does so by giving you new, temporary credentials that you use to sign in and access Google Cloud for the duration of the lab.
To complete this lab, you need:
You are just starting your junior data engineer role. So far you have been helping teams create and manage BigLake assets.
You are expected to have the skills and knowledge for these tasks.
You are asked to help a newly formed development team with some of their initial work on a new project. Specifically, they need a new BigLake table from a Cloud Storage file with the appropriate permissions to limit access to sensitive data columns; you receive the following request to complete the following tasks:
Some standards you should follow:
Each task is described in detail below, good luck!
Create a BigQuery dataset named online_shop that is multi-region in the United States.
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.
Click Check my progress to verify the objective.
Apply the policy tag named sensitive-data-policy to the following columns in the user_online_sessions table:
Click Check my progress to verify the objective.
Click Check my progress to verify the objective.
...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 November 22, 2024
Lab Last Tested November 22, 2024
Copyright 2024 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.
Diese Inhalte sind derzeit nicht verfügbar
Bei Verfügbarkeit des Labs benachrichtigen wir Sie per E-Mail
Sehr gut!
Bei Verfügbarkeit kontaktieren wir Sie per E-Mail
One lab at a time
Confirm to end all existing labs and start this one