Course Overview of Developing Data Models with LookML:

This instructor-led course empowers learners to develop scalable, maintainable, and performant data models using Looker Modeling Language (LookML). Participants will learn how to curate and manage enterprise data within Looker by building dimensions, measures, Explores, dashboards, and derived tables that support consistent business analytics. 

The course covers LookML fundamentals, Looker IDE workflows, Git-based version control, data modeling techniques, custom Explores, derived tables, caching strategies, and data group management. Learners will also explore how LookML transforms SQL into business-friendly analytics experiences for end users. 

Through demonstrations, quizzes, labs, and guided implementation exercises, participants will gain practical experience building and maintaining LookML projects for enterprise-grade business intelligence solutions.

After completing Developing Data Models with LookML, participants will be able to:

  • Define LookML terms, concepts, and building blocks
  • Build dimensions and measures using LookML
  • Create and manage LookML projects using Looker IDE
  • Understand Git integration and version control workflows in Looker
  • Design and build custom Explores for business users
  • Create and manage LookML dashboards
  • Use derived tables for advanced data modeling workflows
  • Implement persistent derived tables and caching strategies
  • Configure datagroups for optimized query performance
  • Build scalable and maintainable enterprise data models in Looker

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Key Features of Developing Data Models with LookML

  • Enterprise Data Modeling with LookML

  • Hands-On Learning Experience

  • LookML Fundamentals and IDE Workflows

  • Dimensions, Measures, and Dashboards

  • Explore Modeling and User Experience

  • Derived Tables and Advanced Modeling

  • Performance Optimization and Caching

  • Google Cloud Analytics Ecosystem Exposure

Who should Attend Developing Data Models with LookML ?

  • Data Developers
  • Analytics Engineers
  • Data Analysts
  • Business Intelligence Developers
  • Cloud Analytics Professionals
  • Looker Developers
  • Professionals responsible for enterprise analytics modeling

Prerequisites of Developing Data Models with LookML

  • Basic understanding of SQL
  • Familiarity with Git concepts
  • Understanding of the Looker business user experience
  • Recommended: Completion of “Analyzing and Visualizing Data in Looker”
  • Interest in analytics engineering and data modeling workflows

    • Why choose CloudThat as your training partner for Developing Data Models with LookML?

    • Specialized Google Cloud Analytics Expertise - CloudThat specializes in cloud and analytics technologies, delivering industry-focused Google Cloud and Looker training programs with practical enterprise implementation experience. 
    • Industry-Recognized Trainers - Our trainers are certified professionals with expertise in Looker, LookML, BigQuery, analytics engineering, and business intelligence solutions. 
    • Hands-On Learning Approach - CloudThat emphasizes practical learning through guided labs, LookML implementation exercises, modeling workflows, and real-world analytics scenarios.
    • Customized Learning Paths - Training programs are designed for data developers, analysts, analytics engineers, and cloud professionals with varying levels of analytics expertise. 
    • Interactive and Practical Sessions - Sessions include demonstrations, collaborative activities, quizzes, implementation walkthroughs, and troubleshooting exercises. 
    • Career and Certification Support - CloudThat supports learners with analytics project guidance, interview preparation, and practical business intelligence implementation strategies. 
    • Updated Industry-Relevant Content- Course content is continuously updated to align with the latest advancements in Looker, LookML, cloud analytics, and data modeling technologies.
    • Trusted by Enterprises Worldwide - Thousands of professionals and organizations trust CloudThat for advanced cloud, analytics, data engineering, and business intelligence training programs.

    Learning Objective of Developing Data Models with LookML

    • Understand LookML architecture and development workflows
    • Build scalable dimensions, measures, and Explores
    • Create and manage LookML dashboards
    • Utilize Git integration and version control workflows
    • Implement advanced derived table strategies
    • Configure caching and datagroups for performance optimization
    • Build reusable and maintainable enterprise data models
    • Improve analytics usability and business reporting workflows
    • Support enterprise analytics governance and consistency
    • Develop scalable business intelligence solutions using Looker

    Course Outline of Developing Data Models with LookML Download Course Outline

    Lecture Content

    • Looker and LookML
    • The Looker User Interface
    • The Looker IDE
    • LookML Project Version Control
    • Git Workflow in Looke
    • How Looker Writes SQL
    • LookML Development Lifecycle
    • SQL and LookML Relationship

    Learning Objectives

    • Articulate the benefits of LookML for data modeling and analytics
    • Identify the primary components of the Looker user interface
    • Define LookML terminology and concepts
    • Understand Git integration within Looker workflows
    • Describe the LookML development lifecycle
    • Explain how LookML generates SQL queries

    Activities

    • 2 Demos
    • 1 Quiz

    Lecture Content

    • Anatomy of a LookML Project
    • Modeling Dimensions
    • Creating Dimensions using LookML
    • Modeling Measures
    • Modeling Measures using LookML
    • Dimension and Measure Modeling Logic
    • LookML Dashboards
    • Dashboard Development Workflows

    Learning Objectives

    • Detail the hierarchical layers within a LookML project
    • Construct dimensions and measures with proper logic and calculations
    • Understand the relationship between IDE development and Explore usage
    • Create and manage LookML dashboards
    • Build enhanced analytics experiences for business users

    Lab Content

    • Lab: Creating Dimensions and Measures with LookML

    Activities

    • 2 Demos
    • 1 Quiz
    • 1 Lab

    Lecture Content

    • Modeling New Explores
    • Using LookML to Filter Explores
    • Understanding Symmetric Aggregation
    • Designing User-Friendly Data Exploration Workflows
    • Explore Optimization Concepts

    Learning Objectives

    • Create custom Explores and filters in Looker IDE
    • Connect Explore models to end-user analytics workflows
    • Understand symmetric aggregation concepts
    • Design scalable and user-friendly analytics experiences

    Activities

    • 1 Quiz

    Lecture Content

    • Introduction to Derived Tables
    • Types of Derived Tables
    • SQL Derived Tables
    • Native Derived Tables
    • Native Derived Table Parameters
    • Persistent Derived Tables (PDTs)
    • Caching and Datagroups
    • Implementing Datagroups in Looker
    • Query Optimization Strategies

    Learning Objectives

    • Understand SQL, native, and persistent derived tables
    • Identify use cases for different derived table types
    • Create derived tables within Looker workflows
    • Configure caching and datagroups for performance optimization
    • Evaluate the impact of caching on Looker performance and scalability

    Lab Content

    • Lab: Creating Derived Tables with LookML

    Activities

    • 2 Demos
    • 1 Quiz
    • 1 Lab

    Certification Details of Developing Data Models with LookML

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    Course ID: 28721

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    FAQs for Developing Data Models with LookML:

    This course is designed for data developers, analytics engineers, and analysts interested in building scalable LookML data models in Looker.

    The course covers LookML fundamentals, dimensions, measures, Explores, dashboards, derived tables, Git workflows, caching, and datagroups.

    Basic familiarity with the Looker business user experience is recommended.

    Yes, a basic understanding of SQL is recommended.

    The course is available as: • Instructor-Led Training (1 Day) • On-Demand Training (Approx. 7 Hours)

    Yes, the course includes practical labs, quizzes, and guided LookML implementation exercises.

    Derived tables are custom tables created within Looker using SQL or LookML logic to support advanced analytics workflows.

    Yes, learners will explore Git-based version control workflows within Looker IDE.

    Yes, the course includes caching, datagroups, and query optimization strategies.

    Yes, this is an intermediate-level course intended for professionals familiar with SQL, analytics, and basic Looker concepts.

    Enquire Now