Course Overview:

LookML is more than a data modeling language—it’s the foundation of visualization, aggregation, and embedded analytics in Looker. This deep dive course is designed to enhance your Looker development skills through lectures and labs. You will learn to build dynamic and modular LookML, manage deployments with DevOps practices, and embed Looker analytics into applications. With hands-on labs and expert-led sessions, you’ll develop the confidence to lead complex Looker implementations. 

After completing this course, participants will be able to:

  • Customize and incrementally refresh SQL and native derived tables
  • Incorporate Liquid syntax for dynamic SQL and formatting
  • Use Looker refinements and extensions for modular LookML
  • Troubleshoot LookML code and improve model performance
  • Apply best practices across your LookML projects
  • Manage Looker deployments using DevOps workflows
  • Embed Looker content securely into web applications

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Key Features:

  • Hands-On Labs: Six labs covering LookML cleanup, PDTs, Liquid syntax, modularization, debugging, and best practices 

  • Real-World Scenarios: Focus on real deployment, embedded analytics, and performance improvement 

  • Advanced Concepts: Explore Liquid templating, Looker DevOps, and embedding strategies 

  • Modular Learning: Topics organized by modules to support progressive understanding 

  • Developer-Centric: Built for Looker developers aiming to advance beyond the basics 

Prerequisites:

To maximize learning outcomes, it’s recommended that learners have:
  • Completion of the “Developing Data Models with LookML” course or equivalent practical experience in Looker LookML development.

    • Why choose CloudThat as your training partner?

    • Specialized GCP Focus: CloudThat specializes in cloud technologies, offering focused and specialized training programs. We are Authorized Trainers for the Google Cloud Platform. This specialization ensures in-depth coverage of GCP services, use cases, best practices, and hands-on experience tailored specifically for GCP.
    • Industry-Recognized Trainers: CloudThat has a strong pool of industry-recognized trainers certified by GCP. These trainers bring real-world experience and practical insights into the training sessions, comprehensively understanding how GCP is applied in different industries and scenarios.
    • Hands-On Learning Approach: CloudThat emphasizes a hands-on learning approach. Learners can access practical labs, real-world projects, and case studies that simulate actual GCP environments. This approach allows learners to apply theoretical knowledge in practical scenarios, enhancing their understanding and skill set.
    • Customized Learning Paths: CloudThat understands that learners have different levels of expertise and varied learning objectives. We offer customized learning paths, catering to beginners, intermediate learners, and professionals seeking advanced GCP skills.
    • Interactive Learning Experience: CloudThat's training programs are designed to be interactive and engaging. We utilize various teaching methodologies like live sessions, group discussions, quizzes, and mentorship to keep learners engaged and motivated throughout the course.
    • Placement Assistance and Career Support: CloudThat often provides placement assistance and career support services. This includes resume building, interview preparation, and connecting learners with job opportunities through our network of industry partners and companies looking for GCP-certified professionals.
    • Continuous Learning and Updates: CloudThat ensures that our course content is regularly updated to reflect the latest trends, updates, and best practices within the GCP ecosystem. This commitment to keeping the content current enables learners to stay ahead in their GCP knowledge.
    • Positive Reviews and Testimonials: Reviews and testimonials from past learners can strongly indicate the quality of training provided. You can Check feedback and reviews about our GCP courses that can provide potential learners with insights into the effectiveness and value of the training.

    Learning Objective:

    • By the end of this course, learners will gain advanced LookML development skills, including working with dynamic derived tables, modularization with refinements, embedding analytics, and applying DevOps practices to Looker projects.

    Course Outline: Download Course Outline

    Topics

    • Looker Review
    • Roles and User Attributes
    • Connecting to a Database
    • LookML Review

    Objectives

    • Review core Looker features and architecture
    • Understand user access via roles and attributes
    • Connect Looker to a new database
    • Review LookML syntax and model structure

    Activities

    • Lecture, Demo, Discussion

    Topics

    • Understanding Derived Tables
    • Adding Persistence
    • Refreshing Incrementally
    • PDTs and Performance

    Objectives

    • Understand how and when to use derived tables
    • Add persistence to derived tables
    • Implement incremental refresh for better performance
    • Evaluate PDTs impact on performance

    Activities

    • Lecture, Demo, Lab

    Topics

    • Core Liquid Concepts and Syntax
    • Custom Links, Drills, and Formatting
    • Templated Filters, Parameters and Dynamic SQL

    Objectives

    • Use Liquid syntax to enable dynamic LookML
    • Create dynamic links, drills, and HTML formatting
    • Use templated filters and parameters

    Activities

    • Lecture, Demo, Lab

    Topics

    • Extensions
    • Refinements
    • Manifests and Localization

    Objectives

    • Use extensions to reuse LookML components
    • Apply refinements to override configurations
    • Implement project manifest and constants

    Activities

    • Lecture, Demo, Lab

    Topics

    • Leverage your IDE
    • Debugging and Common Errors
    • Data Tests
    • Looker and DevOps

    Objectives

    • Debug and fix common LookML issues
    • Add and run data tests
    • ntegrate Looker into DevOps workflows

    Activities

    • Lecture, Demo, Lab

    Topics

    • Looker Best Practices
    • Improving Performance

    Objectives

    • Enhance performance of Looker queries and explores
    • Implement LookML best practices

    Activities

    • Lecture, Demo, Lab

    Topics

    • Explore Embedded Looker Options
    • Using Private and SSO Embedding

    Objectives

    • Understand embedding options for Looker
    • Implement private and SSO embedding scenarios

    Activities

    • Lecture, Demo, Wrap-up

    Certification Details:

      CloudThat Course Completion Certificate

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    Course ID: 26140

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    FAQs:

    It emphasizes advanced LookML skills including modular LookML, dynamic content via Liquid, and embedded analytics.

    2 days of remote instructor-led training, featuring both lectures and hands-on labs.

    No. It’s designed for those who have completed the “Developing Data Models with LookML” course or have equivalent experience.

    Six labs covering LookML cleanup, PDTs, Liquid formatting, modularization, debugging, and embedding analytics.

    Yes, a dedicated module teaches embedded Looker options including SSO and private embedding.

    A working knowledge of LookML and experience with SQL is expected. No additional programming is required.

    Yes. One module specifically covers LookML best practices and performance improvements.

    You’ll explore dynamic SQL generation, templated filters, parameters, custom links, and HTML formatting.

    Yes, CloudThat will issue a certificate upon successful completion of the course.

    Absolutely. The course includes a dedicated session on using IDEs, debugging, and Looker-DevOps integration.

    Enquire Now