Creating Derived Tables with LookML

Looker is a modern data platform in Google Cloud that lets business users analyze and visualize data interactively. LookML developers curate the data used by business users by creating new fields, tables, and views to customize and organize data.

In Looker, LookML developers can use derived tables to create new tables that are not already defined in the underlying database. For example, as a LookML developer, you can create derived tables to summarize details from existing tables, such as order details for each user in an ecommerce dataset.

In this lab, you learn how to create both types of derived tables in LookML: SQL derived tables and native derived tables. You also learn how to define new columns that do not already exist in the underlying data and add them to native derived tables. Last, you learn how to persist derived tables in LookML, so that they can be written back to the underlying database.

For this lab, a project called qwiklabs-ecommerce has been created for you in LookML. This project is based on a mock ecommerce dataset containing information on orders, products, and users.

Lab Link:
https://www.cloudskillsboost.google/p...