GCP300LOOKERDEEPDIVE
Looker Developer Deep Dive
LookML not only serves as the foundation for visualization assets in Looker, but is also capable of dynamic aggregations, incrementally refreshed persistent derived tables, and more. In this course you will practice the skills to be an advanced Looker Developer through guided lectures and independent exercises using sample data.
What you will learn
- Customize and incrementally refresh SQL and native derived tables
- Incorporate Liquid for dynamic SQL, formatting, templated filters, and parameters in Looker
- Use extends and refinements in Looker to modularize and organize your LookML
- Troubleshoot LookML code and improve performance
- Apply Looker best practices to your LookML projects
- Manage Looker deployments using DevOps practices
- Embed Looker content into web applications
Prerequisites
- Completion of the "Developing Data Models with LookML" course or the equivalent experience in using LookML for development in Looker.
Target audience
- Customers
Training Program
7 modules to master the fundamentals
Objectives
- Review key concepts of Looker and LookML development
- Describe roles and user attributes in Looker
- Explain how to connect your Looker instance to a database
Topics covered
- →Looker Review
- →Roles and User Attributes
- →Connecting to a Database
- →LookML Review
Activities
Lab: Starter LookML Cleanup
Objectives
- Define derived tables and advantages of native derived tables
- Maintain derived tables in Looker
- Describe performance implications of different PDT options
Topics covered
- →Understanding Derived Tables
- →Adding Persistence
- →Refreshing Incrementally
- →PDTs and Performance
Activities
Lab: Extending LookML with PDTs and Aggregate Table
Objectives
- Core Liquid Concepts and Syntax
- Custom Links, Drills, and Formatting
- Templated Filters, Parameters and Dynamic SQL
Topics covered
- →Core Liquid Concepts and Syntax
- →Custom Links, Drills, and Formatting
- →Templated Filters, Parameters and Dynamic SQL
Activities
Lab: Enhancing LookML Flexibility with Liquid
Objectives
- Use extends and refinements in Looker to modularize and organize your LookML
- Implement localization into your LookML models
Topics covered
- →Extensions
- →Refinements
- →Manifests and Localization
Activities
Lab: Modularize your LookML
Objectives
- Utilize the Looker IDE to ease development and debugging of LookML.
- Write data tests to ensure validity of your Looker dashboards
- Understand DevOps best practices in Looker
Topics covered
- →Leverage your IDE
- →Debugging and Common Errors
- →Data Tests
- →Looker and DevOps
Activities
Lab: Testing and debugging LookML
Objectives
- Understand Looker best practices
- Implement best practices in LookML to improve performance
Topics covered
- →Looker Best Practices
- →Improving Performance
Activities
Lab: Implementing LookML Best Practices
Objectives
- Explore options for embedding Looker content
- Understand how to use private and SSO embedding
Topics covered
- →Explore Embedded Looker Options
- →Using Private and SSO Embedding
Quality Process
SFEIR Institute's commitment: an excellence approach to ensure the quality and success of all our training programs. Learn more about our quality approach
Teaching Methods Used
- Lectures / Theoretical Slides — Presentation of concepts using visual aids (PowerPoint, PDF).
- Technical Demonstration (Demos) — The instructor performs a task or procedure while students observe.
- Guided Labs — Guided practical exercises on software, hardware, or technical environments.
- Quiz / MCQ — Quick knowledge check (paper-based or digital via tools like Kahoot/Klaxoon).
Evaluation and Monitoring System
The achievement of training objectives is evaluated at multiple levels to ensure quality:
- Continuous Knowledge Assessment : Verification of knowledge throughout the training via participatory methods (quizzes, practical exercises, case studies) under instructor supervision.
- Progress Measurement : Comparative self-assessment system including an initial diagnostic to determine the starting level, followed by a final evaluation to validate skills development.
- Quality Evaluation : End-of-session satisfaction questionnaire to measure the relevance and effectiveness of the training as perceived by participants.
Train multiple employees
- Volume discounts (multiple seats)
- Private or custom session
- On-site or remote