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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...

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$900 USD GSA  $578.09
Course Code GCP-DDM-LOOK
Duration 1 day
Available Formats Classroom, Virtual

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.

Skills Gained

  • Define LookML basic terms and building blocks
  • Modify LookML projects using the Looker Integrated Development Environment (IDE) and project version control
  • Create dimensions and measures to curate data attributes used by business users
  • Create and design Explores to make data accessible to business users
  • Create new tables instantaneously using derived tables
  • Optimize SQL query performance using caching and datagroups in Looker

Who Can Benefit

  • 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.

Course Details

Introduction to Looker and LookML

  • LookML basics, Looker development environment

Creating Dimensions and Measures

  • Dimensions, measures

Project Version Control

  • Git within Looker, project version control

Model Files

  • SQL within Looker, Explores, joins, symmetric aggregations, filters

Derived Tables

  • Derived tables, best practices

Caching and Datagroups

  • Caching, datagroups
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