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Jan 1

Developing Data Models with LookML

January 1 @ 8:00 AM - 5:00 PM AEST

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Developing Data Models with LookML

This instructor led live training 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.

What you Will learn

What's Included?

Instructor Live Training

An instructor will answer your questions

OFFICIAL GOOGLE CLOUD CONTENT

Course content reflects the latest google cloud class

hands on labs

Real world hands on labs provided by Qwiklabs and supported by instructor

CertIficate of completion

Receive official certificate on completion of 80% of labs

Who's this course for?

Level

Language

Duration

Prerequisites

products

Not covered

Course Content

Topics

  • LookML basics, Looker development environment

Objectives

  • Define Looker and the functionality it provides for curating data
  • Define LookML basic terms and building blocks
  • Use the Looker Integrated Development Environment (IDE) to modify LookML
    projects

Activities

  • 1 demo, 1 quiz

Topics

  • Dimensions, measures

Objectives

  • Create dimensions and measures to curate data attributes used by business users

Activites

  • 2 demos, 1 quiz, 1 lab

Topics

  • Git within Looker, project version control

Objectives

  • Implement version control with Git to manage and track changes in LookML
    projects
  • Send LookML changes from a development branch to production

Activities

  • 1 quiz

Topics

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

Objectives

  • Explain how Looker utilizes SQL on the back end to translate user requests to
    query results
  • Create and design Explores to make data accessible to business users
  • Use joins to establish relationships between data tables
  • Leverage symmetric aggregation to ensure the accuracy of aggregated metrics
  • Implement filters to preselect data provided to business users

Activities

  • 1 quiz

Topics

  • Derived tables, best practices

Objectives

  • Define the two types of derived tables in Looker
  • Create ephemeral and persistent derived tables
  • List best practices for creating derived tables

Activities

  • 2 demos, 1 quiz, 1 lab

Topics

  • Caching, datagroups

Objectives

  • Explain how Looker uses caching to optimize SQL query performance
  • Use datagroups to manage caching policies in Looker

Activities

  • 1 demo, 1 quiz

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Have Questions?

No worries. Send us a quick message and we’ll be happy to answer any questions you have.

Ref: C-LOOKDM-I-02

Location

Online

Instructor

Axalon Academy
Email:
training@axalon.io
View Instructor Website

Other

Competencies
Intermediate
Learning Path
Data Analyst