Designing BigQuery Table Schemas for Teradata Professionals

Overview
In BigQuery, you organize data into BigQuery datasets and define the schema (or structure) of each table using column names and data types. The schema of a table can impact query performance and cost in BigQuery, as it determines how quickly and efficiently BigQuery can access and process the data in a table. BigQuery supports flexible schemas, and it is possible to make changes to the schema without having to rewrite the data.

The objective of this lab is to provide Teradata professionals with the necessary knowledge and skills to start designing and implementing effective BigQuery table schemas. Upon completion of this lab, Teradata professionals will have a deeper understanding of how to design, optimize, and query table schemas in BigQuery

In this lab, you create BigQuery datasets and tables to store data, create nested and repeated fields to maintain relationships in denormalized data, and create partitioned and clustered tables to optimize query performance.

In this lab, you learn how to:
Create datasets and tables in BigQuery.
Create and query nested and repeated fields in BigQuery.
Create and query partitioned tables in BigQuery.
Create and query clustered tables in BigQuery.
#gcp #googlecloud #qwiklabs #learntoearn