Developing Data Models with LookML (DDMLML)

 

Course Overview

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.

Who should attend

This course is primarily intended for the following participants:

  • 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 Objectives

  • 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

Follow On Courses

Outline: Developing Data Models with LookML (DDMLML)

Module 1 - Introduction to Looker and LookML

Topics - LookML basics, Looker development environment

  • Define Looker and the functionality it provides for curating data
  • Define LookML basic terms and building blocks
  • Discuss how to modify LookML projects using the Looker Integrated Development Environment (IDE)
  • 1 demo, 1 quiz

Module 2 - Creating Dimensions and Measures

Topics - Dimensions, measures

  • Create dimensions and measures to curate data attributes used by business users
  • 2 demos, 1 quiz, 1 lab

Module 3 - Project Version Control

Topics - Git within Looker, project version control

  • Discuss how to implement version control with Git to manage and track changes in LookML projects
  • Explain how to send LookML changes from a development branch to production
  • 1 quiz

Module 4 - Model Files

Topics - SQL within Looker, Explores, joins, symmetric aggregations, filters

  • Explain how Looker utilizes SQL on the back end to translate user requests to query results
  • Describe how to create and design Explores to make data accessible to business users
  • Identify join parameters that can be used to establish relationships between datatables
  • Discuss the use of symmetric aggregation to ensure the accuracy of aggregated metrics
  • Describe how to implement filters to preselect data provided to business users
  • 1 quiz

Module 5 - Derived Tables

Topics - Derived tables, best practices

  • Define the two types of derived tables in Looker
  • Create ephemeral and persistent derived tables
  • List best practices for creating derived tables
  • 2 demos, 1 quiz, 1 lab

Module 6 - Caching and Datagroups

Topics - Caching, datagroups

  • Explain how Looker uses caching to optimize SQL query performance
  • Describe how datagroups manage caching policies in Looker
  • 1 demo, 1 quiz

Prices & Delivery methods

Online Training

Duration
1 day

Price
  • Online Training: CAD 785
  • Online Training: US $ 595
Classroom Training

Duration
1 day

Price
  • Canada: CAD 785

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Europe

Italy

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