Developing Data Models with LookML

This course empowers you to develop scalable, performant LookML (Looker Modeling Language) models that provide your business users with the standardized, ready-to-use data that they need to answer their questions. Upon completing this course, you will be able to start building and maintaining LookML models to curate and manage data in your organization’s Looker instance.

Objectives

In this course, participants will learn the following skills:

  • Define LookML basic terms and building blocks
  • Use the Looker Integrated Development Environment (IDE) and project version control to modify LookML projects
  • Create dimensions and measures to curate data attributes used by business users
  • Create and design Explores to make data accessible to business users
  • Use derived tables to instantaneously create new tables
  • Use caching and datagroups in Looker to speed up SQL queries

Audience

    This class is intended for the following audience:

  • Data developers who are responsible for data curation and management within their organizations. 
  • Data analysts interested in learning how data developers use LookML to curate and manage data in their organization’s Looker instance

Prerequisites

To get the most out of this course, participants should have a basic understanding of SQL, Git, and the Looker business user experience.

For learners with no previous experience as data explorers in Looker, it is recommended to first complete Analyzing and Visualizing Data in Looker.

Duration

1 day

Investment

Check the next open public class in our enrollment page.
If you are interested in a private training class for your company, contact us.
Developing Data Models with LookML dependencies with other courses and certifications
Developing Data Models with LookML dependencies with other courses and certifications

Course Outline

  • LookML basics, Looker development environment
  • Git within Looker, project version control
  • SQL within Looker, Explores, joins, symmetric aggregations, filters
  • Derived tables, best practices
  • Caching, datagroups