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.

Objectivos

Este curso enseña a los participantes las siguientes habilidades:

  • 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

Público

Esta clase está dirigida a la siguiente audiencia:
  • 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

Prerrequisitos

Para aprovechar al máximo este curso, los participantes deben cumplir con los siguientes criterios:

  • 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.

Duración

1 día

Inversión

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Dependencias de otros cursos y certificaciones con el curso de Developing Data Models with LookML
Dependencias de otros cursos y certificaciones con el curso de Developing Data Models with LookML

Resumen del curso

  • 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