Course Overview of Looker Developer Deep Dive

LookML is more than just a visualization foundation; it is a powerful tool for dynamic aggregations and incrementally refreshed persistent derived tables. This advanced course provides Looker developers with the skills to move beyond basics, focusing on modularity, high-performance modeling, and embedded analytics through guided lectures and independent hands-on exercises.

After completing Looker Developer Deep Dive, participants will be able to:

  • Customize and incrementally refresh SQL and native derived tables
  • Incorporate Liquid logic for dynamic SQL and formatting.
  • Use templated filters and parameters to enhance LookML flexibility.
  • Modularize large LookML projects using Extends and Refinements.
  • Implement localization for global LookML models.
  • Use the Looker IDE for advanced testing, debugging, and data validation
  • Apply DevOps best practices to manage Looker deployments.
  • Embed Looker content securely into external web applications.

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Key Features of Looker Developer Deep Dive

  • Advanced LookML Focus: Specifically designed for experienced developers looking to master dynamic aggregations and Persistent Derived Tables (PDTs).

  • Liquid Integration: Deep dive into using Liquid for templated filters, parameters, and dynamic SQL formatting.

  • Modular Development: Learn to scale LookML projects using advanced techniques like Extends and Refinements.

  • Performance Tuning: Dedicated module on Looker best practices and strategies for improving query performance.

  • Integrated DevOps: Coverage of version control and DevOps practices specifically within the Looker IDE.

  • Embedding Analytics: Explore both Private and SSO embedding options for web applications

Who Should Attend Looker Developer Deep Dive

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.

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    Learning Objective of Looker Developer Deep Dive

    • Advanced Tables: Build and manage SQL and native derived tables with incremental refreshes.
    • Dynamic Logic: Leverage Liquid to create flexible, parameter-driven SQL
    • Project Organization: Use modularity tools to organize and simplify LookML code.
    • Validation & QA: Utilize data tests and the Looker IDE to ensure code validity and performance.
    • Deployment & Governance: Understand and implement Looker DevOps and performance best practices.
    • Connectivity: Connect to databases and manage roles/user attributes effectively.

    Course Outline: Download Course Outline

    Lecture Content

    • Looker platform architectural review
    • Managing Roles, Permissions, and User Attributes for data governance
    • Securely connecting Looker to an enterprise database
    • Core LookML foundational modeling review

    Learning Objectives

    • Review key concepts of Looker administration and LookML development
    • Manage user access control patterns using roles and attributes
    • Connect models to underlying analytical databases securely

    Lab Content

    • NA

    Lecture Content

    • Customizing and compiling SQL Derived Tables vs. Native Derived Tables (NDTs)
    • Optimization strategies using Persistent Derived Tables (PDTs)
    • Configuring and managing incremental updates and refreshes for PDTs
    • Persistence triggers (datagroups and sql_trigger_value)

    Learning Objectives

    • Customize and incrementally refresh both SQL and native derived tables
    • Choose the correct derived table architecture for high-performance modeling

    Lab Content

    • Lab: Creating and Using Derived Tables

    Lecture Content

    • Code reusability utilizing LookML Extensions (extends)
    • Overriding and layering LookML blocks using Refinements (refinements)
    • Project Manifest files (manifest.lkml) and managing remote dependencies
    • Implementing Localization string files (.strings.json) for multi-language global models

    Learning Objectives

    • Use extends and refinements in Looker to modularize, scale, and simplify codebases
    • Implement project manifests and model localization patterns

    Lab Content

    • Lab: Modularize your LookML

    Lecture Content

    • Leveraging advanced features within the Looker IDE for code quality assurance
    • Finding syntax errors, dependency circularities, and debugging common LookML errors
    • Writing automated data_tests blocks to ensure data validity and dashboard reliability
    • Looker-specific DevOps best practices: version control, branching, and deployment managers

    Learning Objectives

    • Utilize the Looker IDE effectively to ease development and debugging of LookML
    • Write automated data tests to validate analytics assertions
    • Apply DevOps and Git-based version control standards within Looker

    Lab Content

    • Lab: Testing and debugging LookML

    Lecture Content

    • Industry standards for organizing and documenting LookML projects
    • Tuning query execution and improving operational dashboard performance
    • Advanced caching policies, symmetric aggregates, and SQL optimization techniques

    Learning Objectives

    • Understand enterprise-grade Looker best practices and coding standards
    • Implement performance-tuning strategies directly into LookML structures

    Lab Content

    • Lab: Implementing LookML Best Practices

    Lecture Content

    • Exploring options for embedding Looker content securely into third-party web apps
    • Understanding the architecture of Private Embedding versus Single Sign-On (SSO) Embedding
    • Constructing secure SSO embed URLs and managing signed user context attributes

    Learning Objectives

    • Explore enterprise options for embedding Looker visualization and reporting assets
    • Understand how to configure and secure private and SSO embedding architectures

    Lab Content

    • NA

    Certification Details: CloudThat Course Completion Certificate will be awarded to all learners who complete the training.

      CloudThat Course Completion Certificate

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    Course ID: 26140

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    FAQs:

    No, this is an "Advanced" level course designed for people who already know LookML.

    Liquid is a templating language used in Looker to make SQL and formatting dynamic, covered in Module 03.

    While it touches on assets, the focus is on the advanced LookML code that powers those assets.

    Yes, the course includes 6 dedicated hands-on labs.

    Module 04 explains these modularization techniques for organizing your code.

    Yes, Module 01 covers roles, user attributes, and secure database connections.

    Yes, Module 07 covers the various options for Private and SSO embedding.

    Module 06 is specifically dedicated to performance best practices.

    Persistent Derived Tables (PDTs) and their advanced customization are covered in Module 02.

    It is a 2-day instructor-led deep dive.

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