Hello Students! As a result of Google’s recent launch of the Programme Learn to Earn Cloud Challenge, there is once more a fantastic opportunity to acquire free Google stuff. Stay with us until the conclusion of this post if you want to find out more information about the challenge.
About Learn to Earn Cloud Challenge
Build and Optimize with Data Warehouses with BigQuery is a skill badge that can be earned on Qwiklabs by using the access code 1q-I2e-getready. In order to participate in the Learn to Earn Cloud Challenge, you must first earn the Build and Optimize with Data Warehouses with a BigQuery skill badge on Qwiklabs. This challenge has been posted on the Google Cloud community channel by emily927, a member of the Google Cloud staff.
It’s time to earn free goodies & swags and earn skill badges by just participating in Learn to Earn Google Cloud Challenge and get hands-on experience with learning materials in the field of Machine Learning, Data Science and Data Warehouses in-demand technology stack.
Build and Optimize Data Warehouses with BigQuery
Complete the Build and Optimize Data Warehouses with BigQuery quest to get a talent badge. You’ll learn how to utilize BigQuery to change your data warehouse, including how to:
- To query and load sample data, use a command-line interface.
- Use SQL, JOINS, and UNIONs to create new reporting tables.
- Divide your dataset into partitions to save money and enhance query performance.
- Make joins and troubleshoot them.
- Un-nest semi-structured datasets after loading, querying and un-nesting them.
- Make use of the Data Catalog.
A skill badge is a Google Cloud-only digital credential that recognizes your competency with Google Cloud products and services by putting your knowledge to the test in an engaging hands-on environment.
To acquire a digital badge that you can share with your network, complete the skill badge quest and the final evaluation challenge lab.
Labs that are included in the coverage of this Google skill badge
- BigQuery: Qwik Start – Command Line
- Creating a Data Warehouse Through Joins and Unions
- Creating Date-Partitioned Tables in BigQuery
- Troubleshooting and Solving Data Join Pitfalls
- Working with JSON, Arrays, and Structs in BigQuery
- Build and Execute MySQL, PostgreSQL, and SQLServer to Data Catalog Connectors
- Build and Optimize Data Warehouses with BigQuery: Challenge Lab